Updated on 2024/03/28

写真a

 
SAYAMA, Hiroki
 
Affiliation
Faculty of Commerce, School of Commerce
Job title
Professor(non-tenure-track)
Degree
Doctor of Science ( 1999.03 The University of Tokyo )
Master of Science ( 1996.03 The University of Tokyo )
Bachelor of Science ( 1994.03 The University of Tokyo )
Profile
Please see below for his full CV:
http://bingweb.binghamton.edu/~sayama/cv.pdf

Research Experience

  • 2018.04
    -
    Now

    Waseda University   Faculty of Commerce   Professor

  • 2017.09
    -
    Now

    Binghamton University, State University of New York   Professor

  • 2012.01
    -
    2017.08

    Binghamton University, State University of New York   Associate Professor

  • 2006.01
    -
    2011.12

    Binghamton University, State University of New York   Assistant Professor

  • 2004.04
    -
    2005.12

    University of Electro-Communications   Department of Human Communication   Associate Professor

  • 2003
    -
    2005

    Nagoya University   Graduate School of Information Science

  • 2003
    -
    2005

    Graduate Schoool of Information Science, Nagoya University Part-time Lecturer

  • 2002.04
    -
    2004.03

    University of Electro-Communications   Department of Human Communication   Assistant Professor

  • 1999.05
    -
    2002.03

    ニューイングランド複雑系研究所 ポストドクトラルフェロー

  • 1999
    -
    2002

    New England Complex Systems Institute Postdoctoral Fellow

  • 2000
    -
    2001

    Harvard University

  • 2000
    -
    2001

    Edwin O. Reischauer Institute of Japanese Studies, Harvard University Associate in Research

  •  
     
     

    Waseda University   Faculty of Commerce   Associate Professor

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Education Background

  • 1994.04
    -
    1999.03

    University of Tokyo   Graduate School of Science   Department of Information Science  

  • 1990.04
    -
    1994.03

    University of Tokyo   Faculty of Science   Department of Information Science  

Professional Memberships

  •  
     
     

    IEEE Systems, Man, & Cybernetics Society

  •  
     
     

    IEEE Computational Intelligence Society

  •  
     
     

    IEEE

  •  
     
     

    Network Science Society

  •  
     
     

    Complex Systems Society

  •  
     
     

    International Society for Artificial Life

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Research Areas

  • Computational science / Mathematical informatics / Intelligent informatics / Web informatics and service informatics

Research Interests

  • systems science

  • adaptive networks

  • social networks

  • social systems

  • interactive systems

  • modeling and simulation

  • complex systems education

  • creativity

  • innovation

  • evolution

  • artificial chemistry

  • artificial life

  • computational social science

  • network science

  • complex systems

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Awards

  • Chancellor's Award for Excellence in Faculty Service

    2022   State University of New York  

  • Outstanding Graduate Director Award

    2022   Binghamton University  

  • Recognition Award for Outstanding Faculty Service

    2021   Thomas J. Watson College of Engineering and Applied Science, Binghamton University  

    Winner: SAYAMA Hiroki

  • ISAL Outstanding Paper of the Decade (2003-2013) Award

    2018   International Society for Artificial Life   Swarm Chemistry

    Winner: SAYAMA Hiroki

  • Best Poster Award

    2017   The 2017 International School and Conference on Network Science (NetSci 2017)  

    Winner: SAYAMA Hiroki

  • First Place, Imagining Science category

    2017   Binghamton University   Visualized for the Blind

    Winner: SAYAMA Hiroki

  • ISAL Exceptional Service Award

    2016   International Society for Artificial Life  

    Winner: SAYAMA Hiroki

  • Lois B. DeFleur Faculty Prize for Academic Achievement

    2016   Binghamton University  

    Winner: SAYAMA Hiroki

  • Chancellor's Award for Excellence in Teaching

    2016   State University of New York  

    Winner: SAYAMA Hiroki

  • Best Contributed Talk

    2015   NetSci 2015 Satellite Symposium on Controlling Complex Networks  

    Winner: SAYAMA Hiroki

  • Best Poster Award

    2011   Eleventh European Conference on Artificial Life (ECAL 11)  

    Winner: SAYAMA Hiroki

  • Best Presentation Award

    2010   IPSJ SIG-Mathematical Modeling and Problem Solving Meeting #81  

    Winner: SAYAMA Hiroki

  • Best Presentation Award

    1996   Fujitsu Fifth Parallel Computing Workshop (PCW'95 Japan)  

    Winner: SAYAMA Hiroki

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Papers

  • Collective group drift in a partial-differential-equation-based opinion dynamics model with biased perception kernels

    Christian Koertje, Hiroki Sayama

    Physical Review E    2024.03

    DOI

    Scopus

  • Sustainability: We need to focus on overall system outcomes rather than simplistic targets

    Len Fisher, Thilo Gross, Helmut Hillebrand, Anders Sandberg, Hiroki Sayama

    People and Nature    2024.01

    DOI

    Scopus

  • Network analysis of discrete emotional states measured via ecological momentary assessment in schizophrenia.

    Gregory P Strauss, Farnaz Zamani-Esfahlani, Ian M Raugh, Lauren Luther, Hiroki Sayama

    European archives of psychiatry and clinical neuroscience   273 ( 8 ) 1863 - 1871  2023.12  [International journal]

     View Summary

    Prior studies demonstrate that schizophrenia (SZ) is associated with abnormalities in positive and negative emotional experience that predict clinical presentation. However, it is unclear whether specific discrete emotions within the broader positive/negative categories are driving those symptom associations. Further, it is also unclear whether specific emotions contribute to symptoms in isolation or via networks of emotional states that dynamically interact across time. The current study used network analysis to evaluate temporally dynamic interactions among discrete emotional states experienced in the real world as assessed via Ecological Momentary Assessment (EMA). Participants included 46 outpatients with chronic SZ and 52 demographically matched healthy controls (CN) who completed 6 days of EMA that captured reports of emotional experience and symptoms derived from monetary surveys and geolocation based symptom markers of mobility and home location. Results indicated that less dense emotion networks were associated with greater severity of negative symptoms, whereas more dense emotion networks were associated with more severe positive symptoms and mania. Additionally, SZ evidenced greater centrality for shame, which was associated with greater severity of positive symptoms. These findings suggest that positive and negative symptoms are associated with distinct profiles of temporally dynamic and interactive emotion networks in SZ. Findings have implications for adapting psychosocial therapies to target specific discrete emotional states in the treatment of positive versus negative symptoms.

    DOI PubMed

    Scopus

  • Visualizing Collective Idea Generation and Innovation Processes in Social Networks.

    Yiding Cao, Yingjun Dong, Minjun Kim 0009, Neil G. MacLaren, Sriniwas Pandey, Shelley D. Dionne, Francis J. Yammarino, Hiroki Sayama

    IEEE Transactions on Computational Social Systems   10 ( 5 ) 2234 - 2243  2023.10

     View Summary

    Collective idea generation and innovation processes are complex and dynamic, involving a large amount of qualitative narrative information that is difficult to monitor, analyze, and visualize using traditional methods. In this study, we developed three new visualization methods for collective idea generation and innovation processes and applied them to data from online social network experiments. The first visualization is the Idea Cloud, which helps monitor collective idea posting activity and intuitively tracks idea clustering and transition. The second visualization is the Idea Geography, which helps understand how the idea space and its utility landscape are structured and how collaboration was performed in that space. The third visualization is the Idea Network, which connects idea dynamics with the social structure of the people who generated them, displaying how social influence among neighbors may have affected collaborative activities and where innovative ideas arose and spread in the social network.

    DOI

    Scopus

    2
    Citation
    (Scopus)
  • Health information exchange network under collaboration, cooperation, and competition: A game-theoretic approach.

    Rawan Shabbar, Hiroki Sayama

    Health care management science   26 ( 3 ) 516 - 532  2023.09  [International journal]

     View Summary

    Health Information Exchange (HIE) network allows securely accessing and sharing healthcare-related information among healthcare providers (HCPs) and payers. HIE services are provided by a non-profit/profit organizations under several subscription plans options. A few studies have addressed the sustainability of the HIE network such that HIE providers, HCPs, and payers remain profitable in the long term. However, none of these studies addressed the coexistence of multiple HIE providers in the network. Such coexistence may have a huge impact on the behavior of healthcare systems in terms of adoption rate and HIE pricing strategies. In addition, in spite of all the effort to maintain cooperation between HIE providers, there is still a chance of competition among them in the market. Possible competition among service providers leads to many concerns about the HIE network sustainability and behavior. In this study, a game-theoretic approach to model the HIE market is proposed. Game-theory is used to simulate the behavior of the three different HIE network agents in the HIE market: HIE providers, HCPs, and payers. Pricing strategies and adoption decisions are optimized using a Linear Programming (LP) mathematical model. Results show that the relation between HIEs in the market is crucial to HCP/Payer adoption decision specially to small HCPs. A small change in the discount rate proposed by a competitive HIE provider will highly affect the decision of HCP/payers to join the HIE network. Finally, competition opened the opportunity for more HCPs to join the network due to reduced pricing. Furthermore, collaborative HIEs provided better performance compared to cooperative in terms of profit and HCP adoption rate by sharing their overall costs and revenues.

    DOI PubMed

    Scopus

  • Markov chain analysis indicates that positive and negative emotions have abnormal temporal interactions during daily life in schizophrenia

    Gregory P. Strauss, Farnaz Zamani Esfahlani, Ian M. Raugh, Lauren Luther, Hiroki Sayama

    Journal of Psychiatric Research   164   344 - 349  2023.08  [International journal]

     View Summary

    Abnormalities in positive and negative emotional experience have been identified in laboratory-based studies in schizophrenia (SZ) and associated with poorer clinical outcomes. However, emotions are not static in daily life-they are dynamic processes that unfold across time and are characterized by temporal interactions. Whether these temporal interactions are abnormal in SZ and associated with clinical outcomes is unclear (i.e., whether the experience of positive/negative emotions at time t increases or decreases the intensity of positive/negative emotions at time t+1). In the current study, participants with SZ (n = 48) and healthy controls (CN; n = 52) completed 6 days of ecological momentary assessment (EMA) surveys that sampled state emotional experience and symptoms. The EMA emotional experience data was submitted to Markov chain analysis to evaluate transitions among combined positive and negative affective states from time t to t+1. Results indicated that: (1) In SZ, the emotion system is more likely to stay in moderate or high negative affect states, regardless of positive affect level; (2) SZ transition to co-activated emotional states more than CN, and once emotional co-activation occurs, the range of emotional states SZ transition to is more variable than CN; (3) Maladaptive transitions among emotional states were significantly correlated with greater positive symptoms and poorer functional outcome in SZ. Collectively, these findings clarify how emotional co-activation occurs in SZ and its effects on the emotion system across time, as well as how negative emotions dampen the ability to sustain positive emotions across time. Treatment implications are discussed.

    DOI PubMed

    Scopus

  • Characterizing Controversiality of Topics Utilizing Eccentricity of Opinions

    Sriniwas Pandey, Hiroki Sayama

    Northeast Journal of Complex Systems   5 ( 1 )  2023.06

     View Summary

    Access to abundant biased information in echo chambers and social bubbles often intensifies opinions to the extremes. The extremization of opinions results in several topics becoming controversial. However, it is very difficult to measure the degree of controversiality of a topic objectively since the controversiality of any topic is subjective and perceived differently from different communities. The absence of an objective measure of controversiality has been a major hindrance in understanding the causes and effects of it. In this work we propose a method to quantify controver-siality of a topic by utilizing eccentricity of opinions on that topic. The eccentricity of an opinion is the amount of strangeness of the opinion relative to other opinions in the social neighborhood. The collective eccentricity of all opinions for a topic works as an indicator of the controversiality of that topic and can be represented by any measure of central tendency. With the help of social network data, we also demonstrate that opinions on several issues related to our routine life show similar trends for diversity though they differ in their controversiality.

    DOI

    Scopus

  • Behaviour and the Origin of Organisms.

    Matthew Egbert, Martin M Hanczyc, Inman Harvey, Nathaniel Virgo, Emily C Parke, Tom Froese, Hiroki Sayama, Alexandra S Penn, Stuart Bartlett

    Origins of life and evolution of the biosphere : the journal of the International Society for the Study of the Origin of Life   53 ( 1-2 ) 87 - 112  2023.05  [International journal]

     View Summary

    It is common in origins of life research to view the first stages of life as the passive result of particular environmental conditions. This paper considers the alternative possibility: that the antecedents of life were already actively regulating their environment to maintain the conditions necessary for their own persistence. In support of this proposal, we describe 'viability-based behaviour': a way that simple entities can adaptively regulate their environment in response to their health, and in so doing, increase the likelihood of their survival. Drawing on empirical investigations of simple self-preserving abiological systems, we argue that these viability-based behaviours are simple enough to precede neo-Darwinian evolution. We also explain how their operation can reduce the demanding requirements that mainstream theories place upon the environment(s) in which life emerged.

    DOI PubMed

    Scopus

  • Effect of Physically Realistic Potential Energy Form on Spatial Pattern Complexity in a Collective Motion Model

    Austin M. Marcus, Hiroki Sayama

    Complexity   2023   8852349 - 14  2023.04

     View Summary

    Collective motion models most often use self-propelled particles, which are known to produce organized spatial patterns via their collective interactions. However, there is less work considering the possible organized spatial patterns achievable by non-self-propelled particles (nondriven), i.e., those obeying energy and momentum conservation. Moreover, it is not known how the potential energy interaction between the particles affects the complexity of the patterns. To address this, in this paper, a collective motion model with a pairwise potential energy function that conserved the total energy and momentum of the particles was implemented. The potential energy function was derived by generalizing the Lennard-Jones potential to reduce to gravity-like and billiard-ball-like potentials at the extremes of its parameter range. The particle model was simulated under a number of parameterizations of this generalized potential, and the average complexity of the spatial pattern produced by each was computed. Complexity was measured by tracking the information needed to describe the particle system at different scales (the complexity profile). It was found that the spatial patterns of the particles were the most complex around a specific ratio in the parameters. This parameter ratio described a characteristic shape of the potential energy function that is capable of producing complex spatial patterns. It is suggested that the characteristic shape of the potential energy produces complex behavior by balancing the likelihood for particles to bond. Furthermore, these results demonstrate that complex spatial patterns are possible even in an isolated system.

    DOI

    Scopus

  • Modeling the Impact of Transportation Availability and Travel Distance on Healthcare Outcomes: A Bagged Random Forest Approach

    Anemone Kasasbeh, Mehmet Yildirim, Amy Booth, Naseem Khan, Hiroki Sayama

    IISE Annual Conference and Expo 2023    2023

     View Summary

    The lack of access to healthcare can lead to poor health outcomes. Factors that prevent patients from getting to their medical care appointments can be associated with an increased risk of adverse health conditions. These factors, such as limited access to transportation and long travel distance, may lead to higher no-show rates and gaps in care. No-shows and gaps in care are claimed to be associated with more emergency department (ED) visits as well as more hospitalizations. In this study, we investigated the impact of travel distance and transportation availability on attending a medical care appointment. Data used in this research were extracted from a community hospital in Broome County, New York. The acquired data spans over the time between January 2021 and July 2022. The response variable in this study is the patient-associated risk score. A bagged random forest meta-ensemble predictive model was developed using a k-fold cross-validation training approach. The model adequacy was assessed using performance measures, including accuracy, sensitivity, and ROC. Results showed that travel distance between a patient’s residential address and their healthcare provider negatively impacted their health outcomes. This finding can help design solutions and interventions such as transportation funding programs and/or expanding bus routes to provide broader transportation coverage.

    DOI

    Scopus

  • Modeling and Analysis of the Lead-Lag Network of Economic Indicators.

    Amanda Goodrick, Hiroki Sayama

    CoRR   abs/2310.16283  2023

    DOI

  • Effects of Network Connectivity and Diversity Distribution on Human Collective Ideation.

    Yiding Cao, Yingjun Dong, Minjun Kim 0009, Neil G. MacLaren, Sriniwas Pandey, Shelley D. Dionne, Francis J. Yammarino, Hiroki Sayama

    CoRR   abs/2307.04284  2023

    DOI

  • Agent Heterogeneity Mediates Extremism in an Adaptive Social Network Model.

    Seth Bullock, Hiroki Sayama

    CoRR   abs/2305.10230  2023

    DOI

  • Generation and Influence of Eccentric Ideas on Social Networks.

    Sriniwas Pandey, Yiding Cao, Yingjun Dong, Minjun Kim, Neil G. MacLaren, Shelley D. Dionne, Francis J. Yammarino, Hiroki Sayama

    CoRR   abs/2304.14459 ( 1 ) 20433 - 20433  2023  [International journal]

     View Summary

    Studying extreme ideas in routine choices and discussions is of utmost importance to understand the increasing polarization in society. In this study, we focus on understanding the generation and influence of extreme ideas in routine conversations which we label "eccentric" ideas. The eccentricity of any idea is defined as the deviation of that idea from the norm of the social neighborhood. We collected and analyzed data from two sources of different nature: public social media and online experiments in a controlled environment. We compared the popularity of ideas against their eccentricity to understand individuals' fascination towards eccentricity. We found that more eccentric ideas have a higher probability of getting a greater number of "likes". Additionally, we demonstrate that the social neighborhood of an individual conceals eccentricity changes in one's own opinions and facilitates generation of eccentric ideas at a collective level.

    DOI PubMed

  • A two-phase model of collective memory decay with a dynamical switching point.

    Naoki Igarashi, Yukihiko Okada, Hiroki Sayama, Yukie Sano

    Scientific reports   12 ( 1 ) 21484 - 21484  2022.12  [International journal]

     View Summary

    Public memories of significant events shared within societies and groups have been conceptualized and studied as collective memory since the 1920s. Thanks to the recent advancement in digitization of public-domain knowledge and online user behaviors, collective memory has now become a subject of rigorous quantitative investigation using large-scale empirical data. Earlier studies, however, typically considered only one dynamical process applied to data obtained in just one specific event category. Here we propose a two-phase mathematical model of collective memory decay that combines exponential and power-law phases, which represent fast (linear) and slow (nonlinear) decay dynamics, respectively. We applied the proposed model to the Wikipedia page view data for articles on significant events in five categories: earthquakes, deaths of notable persons, aviation accidents, mass murder incidents, and terrorist attacks. Results showed that the proposed two-phase model compared favorably with other existing models of collective memory decay in most of the event categories. The estimated model parameters were found to be similar across all the event categories. The proposed model also allowed for detection of a dynamical switching point when the dominant decay dynamics exhibit a phase shift from exponential to power-law. Such decay phase shifts typically occurred about 10 to 11 days after the peak in all of the five event categories.

    DOI PubMed

    Scopus

    2
    Citation
    (Scopus)
  • Multilayer networks with higher-order interaction reveal the impact of collective behavior on epidemic dynamics.

    Jinming Wan, Genki Ichinose, Michael Small, Hiroki Sayama, Yamir Moreno, Changqing Cheng

    Chaos, solitons, and fractals   164   112735 - 112735  2022.11  [International journal]

     View Summary

    The ongoing COVID-19 pandemic has inflicted tremendous economic and societal losses. In the absence of pharmaceutical interventions, the population behavioral response, including situational awareness and adherence to non-pharmaceutical intervention policies, has a significant impact on contagion dynamics. Game-theoretic models have been used to reproduce the concurrent evolution of behavioral responses and disease contagion, and social networks are critical platforms on which behavior imitation between social contacts, even dispersed in distant communities, takes place. Such joint contagion dynamics has not been sufficiently explored, which poses a challenge for policies aimed at containing the infection. In this study, we present a multi-layer network model to study contagion dynamics and behavioral adaptation. It comprises two physical layers that mimic the two solitary communities, and one social layer that encapsulates the social influence of agents from these two communities. Moreover, we adopt high-order interactions in the form of simplicial complexes on the social influence layer to delineate the behavior imitation of individual agents. This model offers a novel platform to articulate the interaction between physically isolated communities and the ensuing coevolution of behavioral change and spreading dynamics. The analytical insights harnessed therefrom provide compelling guidelines on coordinated policy design to enhance the preparedness for future pandemics.

    DOI PubMed

    Scopus

    6
    Citation
    (Scopus)
  • Leadership in the digital era: A review of who, what, when, where, and why

    George C. Banks, Shelley D. Dionne, Marianne Schmid Mast, Hiroki Sayama

    Leadership Quarterly   33 ( 5 )  2022.10

     View Summary

    Leadership as a social influence process has always involved a complex set of phenomena that demands an interdisciplinary lens. Leadership scholarship has now entered into a digital era. In a digital era, the overall phenomenon is changing, as are the tools through which we study it, demanding a new “lens” through which we view leadership. Yet, this raises the question, to what extent is leadership different in a digital era? In acknowledgement of this trend, a special issue was commissioned at The Leadership Quarterly that sought to stimulate the imagination of leadership scholars and practitioners. In the current work, we begin with a brief review of who, what, when, where and why of digital leadership. We cover leadership in informal contexts (e.g., social media), generalization from face-to-face to virtual contexts, computational modeling, the leveraging of technology (e.g., machine learning; Big Data), as well methodological how-to guides. We then plot a path forward for leadership scholars in the dawn of the digital era.

    DOI

    Scopus

    19
    Citation
    (Scopus)
  • Representing and Analyzing the Dynamics of an Agent-Based Adaptive Social Network Model with Partial Integro-Differential Equations

    Hiroki Sayama

    Northeast Journal of Complex Systems   4 ( 1 )  2022.03

     View Summary

    We formulated and analyzed a set of partial integro-differential equations that capture the dynamics of our adaptive network model of social fragmentation involving behavioral diversity of agents. Previous results showed that, if the agents’ cultural tolerance levels were diversified, the social network could remain connected while maintaining cultural diversity. Here we converted the original agent-based model into a continuous equation-based one so we can gain more theoretical insight into the model dynamics. We restricted the node states to 1-D continuous values and assumed the network size was very large. As a result, we represented the whole system as a set of partial integro-differential equations about two continuous functions: population density and connection density. These functions are defined over both the state and the cultural tolerance of nodes. We conducted numerical integration of the developed equations using a custom-made integrator implemented in Julia. The results obtained were consistent with the simulations of the original agent-based adaptive social network model we previously reported, confirming the robustness of the original finding. Specifically, when the variance of cultural tolerance d is large enough, the population with low d maintains the original clusters of cultures/opinions, while the one with high d tends to come to the center and con-nect culturally distant groups. Parameter dependence of the model behavior was also revealed through systematic numerical experiments.

    DOI

    Scopus

  • Detecting Global Community Structure in a COVID-19 Activity Correlation Network.

    Hiroki Sayama

    CoRR   abs/2206.03181   565 - 575  2022

     View Summary

    The global pandemic of COVID-19 over the last 2.5 years have produced an enormous amount of epidemic/public health datasets, which may also be useful for studying the underlying structure of our globally connected world. Here we used the Johns Hopkins University COVID-19 dataset to construct a correlation network of countries/regions and studied its global community structure. Specifically, we selected countries/regions that had at least 100,000 cumulative positive cases from the dataset and generated a 7-day moving average time series of new positive cases reported for each country/region. We then calculated a time series of daily change exponents by taking the day-to-day difference in log of the number of new positive cases. We constructed a correlation network by connecting countries/regions that had positive correlations in their daily change exponent time series using their Pearson correlation coefficient as the edge weight. Applying the modularity maximization method revealed that there were three major communities: (1) Mainly Europe + North America + Southeast Asia that showed similar six-peak patterns during the pandemic, (2) mainly Near/Middle East + Central/South Asia + Central/South America that loosely followed Community 1 but had a notable increase of activities because of the Delta variant and was later impacted significantly by the Omicron variant, and (3) mainly Africa + Central/East Canada + Australia that did not have much activities until a huge spike was caused by the Omicron variant. These three communities were robustly detected under varied settings. Constructing a 3D “phase space” by using the median curves in those three communities for x-y-z coordinates generated an effective summary trajectory of how the global pandemic progressed.

    DOI

  • Social Fragmentation Transitions in Large-Scale Parameter Sweep Simulations of Adaptive Social Networks.

    Hiroki Sayama

    PPAM (2)   13827 LNCS   459 - 469  2022

     View Summary

    Social fragmentation transition is a transition of social states between many disconnected communities with distinct opinions and a well-connected single network with homogeneous opinions. This is a timely research topic with high relevance to various current societal issues. We had previously studied this problem using numerical simulations of adaptive social network models and found that two individual behavioral traits, homophily and attention to novelty, had the most statistically significant impact on the outcomes of social network evolution. However, our previous study was limited in terms of the range of parameter values examined, and possible interactions between multiple behavioral traits were largely ignored. In this study, we conducted a substantially larger-scale parameter sweep numerical experiment of the same model with expanded parameter ranges by an order of magnitude in each parameter dimension, resulting in a total of 116,640 simulation runs. To capture nontrivial interactions among behavioral parameters, we modeled and visualized the dependence of outcome measures on the model parameters using artificial neural networks. Results show that, while the competition between homophily and attention to novelty is still the primary determinant of social fragmentation, another transition plane emerges when individuals have strong social conformity behavior, which was not previously known. This implies that social fragmentation transition can also occur in the homophily-social conformity trade-off, the two behavioral traits that have very similar microscopic individual-level effects but produce very different macroscopic collective-level outcomes, illustrating the nontrivial macroscopic dynamics of complex collective systems.

    DOI

    Scopus

  • Detecting and Forecasting Local Collective Sentiment Using Emojis.

    Mei Fukuda, Kazuyuki Shudo, Hiroki Sayama

    ICWSM Workshops    2022

    DOI

  • Group Size and Group Performance in Small Collaborative Team Settings: An Agent-Based Simulation Model of Collaborative Decision-Making Dynamics.

    Shun Cao, Neil G. MacLaren, Yiding Cao, Jason Marshall, Yingjun Dong, Francis J. Yammarino, Shelley D. Dionne, Michael D. Mumford, Shane Connelly, Robert Martin, Colleen J. Standish, Tanner R. Newbold, Samantha England, Hiroki Sayama, Gregory A. Ruark

    Complexity(Complex.)   2022   8265296 - 16  2022

     View Summary

    The relationship between size and performance of collaborative human small groups has been studied broadly across management, psychology, economics, sociology, and engineering disciplines. However, empirical research findings on this question remain equivocal. Many of the earlier studies centered on empirical human-subject experiments, which inevitably involved many confounding factors. To obtain more theory-driven mechanistic explanations of the linkage between group size and performance, we developed an agent-based simulation model that describes the complex process of collaborative group decision-making on problem-solving tasks. To find better solutions to a problem with given complexity, these agents repeatedly explore and share solution candidates, evaluate and respond to the solutions proposed by others, and update their understanding of the problem by conducting individual local search and incorporating others' proposals. Our results showed that under a condition of ineffective information sharing, group size was negatively related to group performance at the beginning of discussion across each level of problem complexity (i.e., low, medium, and high). However, in the long run, larger groups outperformed smaller groups for the problem with medium complexity and equally well for the problem with low complexity because larger groups developed higher solution diversity. For the problem with high complexity, the higher solution diversity led to more disagreements which in turn hindered larger groups' collaborative problem-solving ability. Our results also suggested that, in small collaborative team settings, effective information sharing can significantly improve group performance for groups of any size, especially for larger groups. This model provides a unified, mechanistic explanation of the conflicting observations reported in the existing empirical literature.

    DOI

    Scopus

    3
    Citation
    (Scopus)
  • Analysis and Visualization of High-Dimensional Dynamical Systems' Phase Space Using a Network-Based Approach.

    Shane St. Luce, Hiroki Sayama

    Complexity(Complex.)   2022   3937475 - 11  2022

     View Summary

    The concept of attractors is considered critical in the study of dynamical systems as they represent the set of states that a system gravitates toward. However, it is generally difficult to analyze attractors in complex systems due to multiple reasons including chaos, high-dimensionality, and stochasticity. This paper explores a novel approach to analyzing attractors in complex systems by utilizing networks to represent phase spaces. We accomplish this by discretizing phase space and defining node associations with attractors by finding sink strongly connected components (SSCCs) within these networks. Moreover, the network representation of phase space facilitates the use of well-established techniques of network analysis to study the phase space of a complex system. We show the latter by introducing a new node-based metric called attractivity which can be used in conjunction with the SSCC as they are highly correlated. We demonstrate the proposed method by applying it to several chaotic dynamical systems and a large-scale agent-based social simulation model.

    DOI

    Scopus

    2
    Citation
    (Scopus)
  • Machine Learning Identifies Digital Phenotyping Measures Most Relevant to Negative Symptoms in Psychotic Disorders: Implications for Clinical Trials.

    Sayli M Narkhede, Lauren Luther, Ian M Raugh, Anna R Knippenberg, Farnaz Zamani Esfahlani, Hiroki Sayama, Alex S Cohen, Brian Kirkpatrick, Gregory P Strauss

    Schizophrenia bulletin   48 ( 2 ) 425 - 436  2021.12  [International journal]

     View Summary

    BACKGROUND: Digital phenotyping has been proposed as a novel assessment tool for clinical trials targeting negative symptoms in psychotic disorders (PDs). However, it is unclear which digital phenotyping measurements are most appropriate for this purpose. AIMS: Machine learning was used to address this gap in the literature and determine whether: (1) diagnostic status could be classified from digital phenotyping measures relevant to negative symptoms and (2) the 5 negative symptom domains (anhedonia, avolition, asociality, alogia, and blunted affect) were differentially classified by active and passive digital phenotyping variables. METHODS: Participants included 52 outpatients with a PD and 55 healthy controls (CN) who completed 6 days of active (ecological momentary assessment surveys) and passive (geolocation, accelerometry) digital phenotyping data along with clinical ratings of negative symptoms. RESULTS: Machine learning algorithms classifying the presence of a PD diagnosis yielded 80% accuracy for cross-validation in H2O AutoML and 79% test accuracy in the Recursive Feature Elimination with Cross Validation feature selection model. Models classifying the presence vs absence of clinically significant elevations on each of the 5 negative symptom domains ranged in test accuracy from 73% to 91%. A few active and passive features were highly predictive of all 5 negative symptom domains; however, there were also unique predictors for each domain. CONCLUSIONS: These findings suggest that negative symptoms can be modeled from digital phenotyping data recorded in situ. Implications for selecting the most appropriate digital phenotyping variables for use as outcome measures in clinical trials targeting negative symptoms are discussed.

    DOI PubMed

    Scopus

    13
    Citation
    (Scopus)
  • A comprehensive review of Rasch measurement in language assessment: Recommendations and guidelines for research

    Vahid Aryadoust, Li Ying Ng, Hiroki Sayama

    Language Testing   38 ( 1 ) 6 - 40  2021.01

     View Summary

    Over the past decades, the application of Rasch measurement in language assessment has gradually increased. In the present study, we coded 215 papers using Rasch measurement published in 21 applied linguistics journals for multiple features. We found that seven Rasch models and 23 software packages were adopted in these papers, with many-facet Rasch measurement (n = 100) and Facets (n = 113) being the most frequently used Rasch model and software, respectively. Significant differences were detected between the number of papers that applied Rasch measurement to different language skills and components, with writing (n = 63) and grammar (n = 12) being the most and least frequently investigated, respectively. In addition, significant differences were found between the number of papers reporting person separation (n = 73, not reported: n = 142) and item separation (n = 59, not reported: n = 156) and those that did not. An alarming finding was how few papers reported unidimensionality check (n = 57 vs 158) and local independence (n = 19 vs 196). Finally, a multilayer network analysis revealed that research involving Rasch measurement has created two major discrete communities of practice (clusters), which can be characterized by features such as language skills, the Rasch models used, and the reporting of item reliability/separation vs person reliability/separation. Cluster 1 was accordingly labelled the production and performance cluster, whereas cluster 2 was labelled the perception and language elements cluster. Guidelines and recommendations for analyzing unidimensionality, local independence, data-to-model fit, and reliability in Rasch model analysis are proposed.

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  • Network-Based Phase Space Analysis of the El Farol Bar Problem.

    Shane St. Luce, Hiroki Sayama

    Artificial Life   27 ( 2 ) 113 - 130  2021  [International journal]

     View Summary

    The El Farol Bar problem highlights the issue of bounded rationality through a coordination problem where agents must decide individually whether or not to attend a bar without prior communication. Each agent is provided a set of attendance predictors (or decision-making strategies) and uses the previous bar attendances to guess bar attendance for a given week to determine if the bar is worth attending. We previously showed how the distribution of used strategies among the population settles into an attractor by using a spatial phase space. However, this approach was limited as it required N - 1 dimensions to fully visualize the phase space of the problem, where N is the number of strategies available. Here we propose a new approach to phase space visualization and analysis by converting the strategy dynamics into a state transition network centered on strategy distributions. The resulting weighted, directed network gives a clearer representation of the strategy dynamics once we define an attractor of the strategy phase space as a sink-strongly connected component. This enables us to study the resulting network to draw conclusions about the performance of the different strategies. We find that this approach not only is applicable to the El Farol Bar problem, but also addresses the dimensionality issue and is theoretically applicable to a wide variety of discretized complex systems.

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  • Life Worth Mentioning: Complexity in Life-Like Cellular Automata.

    Eric Peña, Hiroki Sayama

    Artificial Life   27 ( 2 ) 105 - 112  2021  [International journal]

     View Summary

    Cellular automata (CA) have been lauded for their ability to generate complex global patterns from simple local rules. The late English mathematician, John Horton Conway, developed his illustrious Game of Life (Life) CA in 1970, which has since remained one of the most quintessential CA constructions-capable of producing a myriad of complex dynamic patterns and computational universality. Life and several other Life-like rules have been classified in the same group of aesthetically and dynamically interesting CA rules characterized by their complex behaviors. However, a rigorous quantitative comparison among similarly classified Life-like rules has not yet been fully established. Here we show that Life is capable of maintaining as much complexity as similar rules while remaining the most parsimonious. In other words, Life contains a consistent amount of complexity throughout its evolution, with the least number of rule conditions compared to other Life-like rules. We also found that the complexity of higher density Life-like rules, which themselves contain the Life rule as a subset, form a distinct concave density-complexity relationship whereby an optimal complexity candidate is proposed. Our results also support the notion that Life functions as the basic ingredient for cultivating the balance between structure and randomness to maintain complexity in 2D CA for low- and high-density regimes, especially over many iterations. This work highlights the genius of John Horton Conway and serves as a testament to his timeless marvel, which is referred to simply as: Life.

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  • Detecting Dynamic States of Temporal Networks Using Connection Series Tensors

    Shun Cao, Hiroki Sayama, Pietro De Lellis

    Complexity   abs/2007.12756  2020.12

     View Summary

    Many temporal networks exhibit multiple system states, such as weekday and
    weekend patterns in social contact networks. The detection of such distinct
    states in temporal network data has recently been explored as it helps reveal
    underlying dynamical processes. A commonly used method is network aggregation
    over a time window, which aggregates a subsequence of multiple network
    snapshots into one static network. This method, however, necessarily discards
    temporal dynamics within the time window. Here we develop a new method for
    detecting dynamic states in temporal networks using information regarding the
    timeline of contacts between each pair of nodes. We apply a similarity measure
    informed by the techniques of processing time series and community detection to
    sequentially discompose a given temporal network into multiple dynamic states
    (including repeated ones). Experiments with empirical temporal network data
    demonstrated that our method outperformed the conventional approach using
    simple network aggregation in revealing interpretable system states. In
    addition, our method allows users to analyze hierarchical temporal structures
    and to uncover dynamic state at different spatial/temporal resolutions.

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  • Testing the babble hypothesis: Speaking time predicts leader emergence in small groups

    Neil G. MacLaren, Francis J. Yammarino, Shelley D. Dionne, Hiroki Sayama, Michael D. Mumford, Shane Connelly, Robert W. Martin, Tyler J. Mulhearn, E. Michelle Todd, Ankita Kulkarni, Yiding Cao, Gregory A. Ruark

    Leadership Quarterly   31 ( 5 )  2020.10

     View Summary

    The large, positive correlation between speaking time and leader emergence is well-established. As such, some authors have argued for a “babble hypothesis” of leadership, suggesting that only the quantity of speaking, not its quality, determines leader emergence. However, previous tests of this notion may have been problematic. Some studies have asserted a causal effect of speaking time on leader emergence based on experimental studies, but have limited participant communication, access to reliable information, or both. Other studies have used more ecologically valid designs, but have not always controlled for relevant participant traits or roles, suggesting potential endogeneity effects. Testing the babble hypothesis thus requires a study that is both ecologically valid and supports strong inference. The current study fills that gap and finds that speaking time retains its direct effect on leader emergence when accounting for intelligence, personality, gender, and the endogeneity of speaking time.

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  • Mathematically Modeling Anhedonia in Schizophrenia: A Stochastic Dynamical Systems Approach

    Gregory P Strauss, Farnaz Zamani Esfahlani, Eric Granholm, Jason Holden, Katherine Frost Visser, Lisa A Bartolomeo, Hiroki Sayama

    Schizophrenia Bulletin   43 ( 5 ) S99 - S99  2020.09  [Refereed]  [International journal]

     View Summary

    OBJECTIVE: Anhedonia, traditionally defined as a diminished capacity for pleasure, is a core symptom of schizophrenia (SZ). However, modern empirical evidence indicates that hedonic capacity may be intact in SZ and anhedonia may be better conceptualized as an abnormality in the temporal dynamics of emotion. METHOD: To test this theory, the current study used ecological momentary assessment (EMA) to examine whether abnormalities in one aspect of the temporal dynamics of emotion, sustained reward responsiveness, were associated with anhedonia. Two experiments were conducted in outpatients diagnosed with SZ (n = 28; n = 102) and healthy controls (n = 28; n = 71) who completed EMA reports of emotional experience at multiple time points in the day over the course of several days. Markov chain analyses were applied to the EMA data to evaluate stochastic dynamic changes in emotional states to determine processes underlying failures in sustained reward responsiveness. RESULTS: In both studies, Markov models indicated that SZ had deficits in the ability to sustain positive emotion over time, which resulted from failures in augmentation (ie, the ability to maintain or increase the intensity of positive emotion from time t to t+1) and diminution (ie, when emotions at time t+1 are opposite in valence from emotions at time t, resulting in a decrease in the intensity of positive emotion over time). Furthermore, in both studies, augmentation deficits were associated with anhedonia. CONCLUSIONS: These computational findings clarify how abnormalities in the temporal dynamics of emotion contribute to anhedonia.

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  • Simulating Systems Thinking under Bounded Rationality

    Mark W. Sellers, Hiroki Sayama, Andreas D. Pape

    Complexity   2020   3469263 - 12  2020.09

     View Summary

    Brian Arthur's El Farol bar model of bounded rationality provides a simple computer model of decision making in a complex, dynamic, and self-organized environment. Can systems thinking provide a viable alternative strategy to traditional methods for dealing with these types of problems? Nine different agents, designed from both traditional and systems perspectives, compete in fifteen variants of the El Farol environment and their performance in 4 categories-Winner, Top Performers, Competitive, and Vulnerable-is compared. We show that systems thinking is a competitive strategy that is, at least, on par with traditional strategies and may be less vulnerable to elimination or ruin. However, there are two consequential elements that emerge. First, all strategies have some environments where they succeed and others where they fail. Second, as the population of practitioners adopts these adaptive, systems-based strategies, the environment exhibits new behaviors with a new set of unintended consequences.

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  • Mathematically Modeling Anhedonia in Schizophrenia: A Stochastic Dynamical Systems Approach

    Gregory P. Strauss, Farnaz Zamani Esfahlani, Eric Granholm, Jason Holden, Katherine Frost Visser, Lisa A. Bartolomeo, Hiroki Sayama

    SCHIZOPHRENIA BULLETIN   46 ( 5 ) 1191 - 1201  2020.09

     View Summary

    Objective: Anhedonia, traditionally defined as a diminished capacity for pleasure, is a core symptom of schizophrenia (SZ). However, modern empirical evidence indicates that hedonic capacity may be intact in SZ and anhedonia may be better conceptualized as an abnormality in the temporal dynamics of emotion.Method: To test this theory, the current study used ecological momentary assessment (EMA) to examine whether abnormalities in one aspect of the temporal dynamics of emotion, sustained reward responsiveness, were associated with anhedonia. Two experiments were conducted in outpatients diagnosed with SZ (n = 28; n = 102) and healthy controls (n = 28; n = 71) who completed EMA reports of emotional experience at multiple time points in the day over the course of several days. Markov chain analyses were applied to the EMA data to evaluate stochastic dynamic changes in emotional states to determine processes underlying failures in sustained reward responsiveness.Results: In both studies, Markov models indicated that SZ had deficits in the ability to sustain positive emotion over time, which resulted from failures in augmentation (ie, the ability to maintain or increase the intensity of positive emotion from time t to t+1) and diminution (ie, when emotions at time t+1 are opposite in valence from emotions at time t, resulting in a decrease in the intensity of positive emotion over time). Furthermore, in both studies, augmentation deficits were associated with anhedonia.Conclusions: These computational findings clarify how abnormalities in the temporal dynamics of emotion contribute to anhedonia.

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    15
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  • The Role of Criticality of Gene Regulatory Networks in Morphogenesis

    Hyobin Kim, Hiroki Sayama

    IEEE Transactions on Cognitive and Developmental Systems   12 ( 3 ) 390 - 400  2020.09

     View Summary

    Gene regulatory network (GRN)-based morphogenetic models have recently gained an increasing attention. However, the relationship between microscopic properties of intracellular GRNs and macroscopic properties of morphogenetic systems has not been fully understood yet. Here, we propose a theoretical morphogenetic model representing an aggregation of cells, and reveal the relationship between criticality of GRNs and morphogenetic pattern formation. In our model, the positions of the cells are determined by spring-mass-damper kinetics. Each cell has an identical Kauffman's NK random Boolean network (RBN) as its GRN. We varied the properties of GRNs from ordered, through critical, to chaotic by adjusting node in-degree K. We randomly assigned four cell fates to the attractors of RBNs for cellular behaviors. By comparing diverse morphologies generated in our morphogenetic systems, we investigated what the role of the criticality of GRNs is in forming morphologies. We found that nontrivial spatial patterns were generated most frequently when GRNs were at criticality. Our finding indicates that the criticality of GRNs facilitates the formation of nontrivial morphologies in GRN-based morphogenetic systems.

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  • Network Analysis Indicates That Avolition Is the Most Central Domain for the Successful Treatment of Negative Symptoms: Evidence From the Roluperidone Randomized Clinical Trial

    Gregory P Strauss, Farnaz Zamani Esfahlani, Hiroki Sayama, Brian Kirkpatrick, Mark G Opler, Jay B Saoud, Michael Davidson, Remy Luthringer

    Schizophrenia Bulletin   46 ( 4 ) 964 - 970  2020.07  [International journal]

     View Summary

    A recent conceptual development in schizophrenia is to view its manifestations as interactive networks rather than individual symptoms. Negative symptoms, which are associated with poor functional outcome and reduced rates of recovery, represent a critical need in schizophrenia therapeutics. MIN101 (roluperidone), a compound in development, demonstrated efficacy in the treatment of negative symptoms in schizophrenia. However, it is unclear how the drug achieved its effect from a network perspective. The current study evaluated the efficacy of roluperidone from a network perspective. In this randomized clinical trial, participants with schizophrenia and moderate to severe negative symptoms were randomly assigned to roluperidone 32 mg (n = 78), 64 mg (n = 83), or placebo (N = 83). Macroscopic network properties were evaluated to determine whether roluperidone altered the overall density of the interconnections among symptoms. Microscopic properties were evaluated to examine which individual symptoms were most influential (ie, interconnected) on other symptoms in the network and are responsible for successful treatment effects. Participants receiving roluperidone did not differ from those randomized to placebo on macroscopic properties. However, microscopic properties (degree and closeness centrality) indicated that avolition was highly central in patients receiving placebo and that roluperidone reduced this level of centrality. These findings suggest that decoupling the influence of motivational processes from other negative symptom domains is essential for producing global improvements. The search for pathophysiological mechanisms and targeted treatment development should be focused on avolition, with the expectation of improvement in the entire constellation of negative symptoms if avolition is effectively treated.

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  • A polynomial-time deterministic approach to the travelling salesperson problem

    Ali Jazayeri, Hiroki Sayama

    International Journal of Parallel, Emergent and Distributed Systems   35 ( 4 ) 454 - 460  2020.07

     View Summary

    We propose a new polynomial-time deterministic algorithm that produces an approximated solution for the travelling salesperson problem. The proposed algorithm ranks cities based on their priorities calculated using a power function of means and standard deviations of their distances from other cities and then connects the cities to their neighbours in the order of their priorities. When connecting a city, a neighbour is selected based on their neighbours' priorities calculated as another power function that additionally includes their distance from the focal city to be connected. This repeats until all the cities are connected into a single loop. The time complexity of the proposed algorithm is (Formula presented.), where n is the number of cities. Numerical evaluation shows that, despite its simplicity, the proposed algorithm produces shorter tours with less time complexity than other conventional tour construction heuristics. The proposed algorithm can be used by itself or as an initial tour generator for other more complex heuristic optimisation algorithms.

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  • Enhanced ability of information gathering may intensify disagreement among groups

    Hiroki Sayama

    Physical Review E   102 ( 1-1 ) 012303 - 012303  2020.07  [International journal]

     View Summary

    Today's society faces widening disagreement and conflicts among constituents with incompatible views. Escalated views and opinions are seen not only in radical ideology or extremism but also in many other scenes of our everyday life. Here we show that widening disagreement among groups may be linked to the advancement of information communication technology by analyzing a mathematical model of population dynamics in a continuous opinion space. We adopted the interaction kernel approach to model enhancement of people's information-gathering ability and introduced a generalized nonlocal gradient as individuals' perception kernel. We found that the characteristic distance between population peaks becomes greater as the wider range of opinions becomes available to individuals or the more attention is attracted to opinions distant from theirs. These findings may provide a possible explanation for why disagreement is growing in today's increasingly interconnected society, without attributing its cause only to specific individuals or events.

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    3
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  • Greetings from the New Chief Editor

    Hiroki Sayama

    Complexity   2020   7291532 - 2  2020.06

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  • An Agent-Based Model of Leader Emergence and Leadership Perception within a Collective

    Shun Cao, Neil G. MacLaren, Yiding Cao, Yingjun Dong, Hiroki Sayama, Francis J. Yammarino, Shelley D. Dionne, Michael D. Mumford, Shane Connelly, Robert Martin, Colleen J. Standish, Tanner R. Newbold, Samantha England, Gregory A. Ruark

    Complexity   2020   6857891 - 11  2020.04

     View Summary

    Effective teamwork in an initially leaderless group requires a high level of collective leadership emerging from dynamic interactions among group members. Leader emergence is a crucial topic in collective leadership, yet it is challenging to investigate as the problem context is typically highly complex and dynamic. Here, we explore leadership emergence and leadership perception by means of computational simulations whose assumptions and parameters were informed by empirical research and human-subject experiments. Our agent-based model describes the process of group planning. Each agent is assigned with three key attributes: talkativeness, intelligence, and credibility. An agent can propose a suggestion to modify the group plan as a speaker or respond and evaluate others' suggestions and leadership as a listener. Simulation results suggested that agents with high values of talkativeness, intelligence, and credibility tended to be perceived as leaders by their peers. Results also showed that talkativeness may be the most significant and instantaneous predictor for leader emergence of the three investigated attributes: talkativeness, intelligence, and credibility. In terms of group performance, smaller groups may outperform larger groups regarding their problem-solving ability in the beginning, but their performance tends to be of no significant difference in a long run. These results match the empirical literature and offer a mechanistic, operationalized description of the collective leadership processes.

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    6
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  • Self-Organization and Artificial Life.

    Carlos Gershenson, Vito Trianni, Justin Werfel, Hiroki Sayama

    Artificial life   26 ( 3 ) 391 - 408  2020  [Refereed]  [International journal]

     View Summary

    Self-organization can be broadly defined as the ability of a system to display ordered spatiotemporal patterns solely as the result of the interactions among the system components. Processes of this kind characterize both living and artificial systems, making self-organization a concept that is at the basis of several disciplines, from physics to biology and engineering. Placed at the frontiers between disciplines, artificial life (ALife) has heavily borrowed concepts and tools from the study of self-organization, providing mechanistic interpretations of lifelike phenomena as well as useful constructivist approaches to artificial system design. Despite its broad usage within ALife, the concept of self-organization has been often excessively stretched or misinterpreted, calling for a clarification that could help with tracing the borders between what can and cannot be considered self-organization. In this review, we discuss the fundamental aspects of self-organization and list the main usages within three primary ALife domains, namely "soft" (mathematical/computational modeling), "hard" (physical robots), and "wet" (chemical/biological systems) ALife. We also provide a classification to locate this research. Finally, we discuss the usefulness of self-organization and related concepts within ALife studies, point to perspectives and challenges for future research, and list open questions. We hope that this work will motivate discussions related to self-organization in ALife and related fields.

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    27
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  • Detecting Dynamic States of Temporal Networks Using Connection Series Tensors.

    Shun Cao, Hiroki Sayama

    Complexity(Complex.)   2020   9649310 - 15  2020

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    4
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  • Graph product representation of organism-environment couplings in evolution

    Hiroki Sayama

    Proceedings of the 2019 Conference on Artificial Life: How Can Artificial Life Help Solve Societal Challenges, ALIFE 2019     412 - 413  2020

     View Summary

    We present a theoretical framework that mathematically formulates the evolutionary dynamics of organism-environment couplings using graph product multilayer networks, i.e., networks obtained by “multiplying” factor networks using some graph product operator. In this framework, one factor network represents different options of environments and their mutual physical reachability, and another factor network represents possible types of organisms and their mutual evolutionary reachability. The organism-environment coupling space is given by a Cartesian product of these two factor networks, and the nodes of the product network represent specific organism-environment combinations. We studied a simple evolutionary model using a reaction-diffusion equation on this organism-environment coupling space. We numerically calculated correlations between the inherent fitness of organisms and the actual average fitness obtained from the graph product-based evolutionary model, varying the spatial diffusion rate while keeping the type diffusion rate small. Results demonstrated that, when the spatial diffusion is sufficiently slow, the correlation between inherent and actual fitnesses drops significantly, where it is no longer valid to assume that fitness can be attributed only to organisms.

  • Suppleness and open-endedness for social sustainability

    Hiroki Sayama

    Proceedings of the 2019 Conference on Artificial Life: How Can Artificial Life Help Solve Societal Challenges, ALIFE 2019     28 - 29  2020

     View Summary

    One of the research questions in ALife that could contribute greatly to social sustainability issues is how dynamic meta-states of a complex system may be sustained through continual adaptive changes, or suppleness (Bedau, 1998). The idea of sustainability by suppleness is fundamentally different from conventional ideas of sustainability by robustness or resilience, and it is directly linked to open-endedness, a topic that has recently attracted significant attention in the ALife community (Taylor et al., 2016). Understanding and implementing mechanisms of suppleness and open-endedness may provide novel perspectives of many of today's socio-economic, socio-ecological and socio-technological problems that call for new strategies to cope with inevitable environmental/contextual changes. This short essay provides a non-exhaustive list of research questions on this topic and encourages ALife researchers to play a leading role in this interdisciplinary collaboration endeavor.

  • Adaptive control and optimization of multi-agent networks

    Nasim Nezamoddini, Hiroki Sayama

    Proceedings of the 2020 IISE Annual Conference     1418 - 1423  2020

     View Summary

    This research proposes a novel technique for distributed control and optimization of the networked systems considering the uncertainties associated with internal complex dynamics and external interactions with the environment. The proposed technique applies a distributed multi-agent framework that minimizes the overall objective of the system subject to the limitations on the shared resources. In this framework, each agent tries to optimize its decisions and improve the learning strategy based on artificial neural networks (ANN) without having access to the statistical distributions of the involved parameters. Comprehensive experiments are implemented to investigate the effects of the learning mechanism and the level of uncertainties. The efficiency of the technique is tested by comparing the proposed technique with the existing traditional network optimization techniques. The proposed technique can be utilized in a variety of applications such as min cost flow problems, disease propagation models, and distributed controls over man-made networks such as supply chain and power grid.

  • Hot-Get-Richer Network Growth Model.

    Faisal Nsour, Hiroki Sayama

    CoRR   abs/2010.08659  2020

     View Summary

    Under preferential attachment (PA) network growth models late arrivals are at
    a disadvantage with regard to their final degrees. Previous extensions of PA
    have addressed this deficiency by either adding the notion of node fitness to
    PA, usually drawn from some fitness score distributions, or by using fitness
    alone to control attachment. Here we introduce a new dynamical approach to
    address late arrivals by adding a recent-degree-change bias to PA so that nodes
    with higher relative degree change in temporal proximity to an arriving node
    get an attachment probability boost. In other words, if PA describes a
    rich-get-richer mechanism, and fitness-based approaches describe
    good-get-richer mechanisms, then our model can be characterized as a
    hot-get-richer mechanism, where hotness is determined by the rate of degree
    change over some recent past. The proposed model produces much later
    high-ranking nodes than the PA model and, under certain parameters, produces
    networks with structure similar to PA networks.

  • Speaker Diarization Using Stereo Audio Channels: Preliminary Study on Utterance Clustering.

    Yingjun Dong, Neil G. MacLaren, Yiding Cao, Francis J. Yammarino, Shelley D. Dionne, Michael D. Mumford, Shane Connelly, Hiroki Sayama, Gregory A. Ruark

    CoRR   abs/2009.05076  2020

  • Hot-Get-Richer Network Growth Model.

    Faisal Nsour, Hiroki Sayama

    Complex Networks & Their Applications IX - Volume 2, Proceedings of the Ninth International Conference on Complex Networks and Their Applications   944   532 - 543  2020

     View Summary

    Under preferential attachment (PA) network growth models late arrivals are at a disadvantage with regard to their final degrees. Previous extensions of PA have addressed this deficiency by either adding the notion of node fitness to PA, usually drawn from some fitness score distributions, or by using fitness alone to control attachment. Here we introduce a new dynamical approach to address late arrivals by adding a recent-degree-change bias to PA so that nodes with higher relative degree change in temporal proximity to an arriving node get an attachment probability boost. In other words, if PA describes a rich-get-richer mechanism, and fitness-based approaches describe good-get-richer mechanisms, then our model can be characterized as a hot-get-richer mechanism, where hotness is determined by the rate of degree change over some recent past. The proposed model produces much later high-ranking nodes than the PA model and, under certain parameters, produces networks with structure similar to PA networks.

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  • Efficient sentinel surveillance strategies for preventing epidemics on networks

    Ewan Colman, Daniela Paolotti, Petter Holme, Hiroki Sayama, Carlos Gershenson

    PLOS Computational Biology   15 ( 11 ) e1007517  2019.11  [International journal]

     View Summary

    Surveillance plays a crucial role in preventing emerging infectious diseases from becoming epidemic. In circumstances where it is possible to monitor the infection status of certain people, transport hubs, or hospitals, early detection of the disease allows interventions to be implemented before most of the damage can occur, or at least its impact can be mitigated. This paper addresses the question of which nodes we should select in a network of individuals susceptible to some infectious disease in order to minimize the number of casualties. By simulating disease outbreaks on a collection of empirical and synthetic networks we show that the best strategy depends on topological characteristics of the network. For highly modular or spatially embedded networks it is better to place the sentinels on nodes distributed across different regions. However, if the degree heterogeneity is high, then a strategy that targets network hubs is preferred. We further consider the consequences of having an incomplete sample of the network and demonstrate that the value of new information diminishes as more data is collected. Finally we find further marginal improvements using two heuristics informed by known results in graph theory that exploit the fragmented structure of sparse network data.

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    12
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  • Network Analysis Reveals Which Negative Symptom Domains Are Most Central in Schizophrenia vs Bipolar Disorder

    Gregory Paul Strauss, Farnaz Zamani Esfahlani, Brian Kirkpatrick, Daniel N Allen, James M Gold, Katherine Frost Visser, Hiroki Sayama

    Schizophrenia Bulletin   45 ( 6 ) 1319 - 1330  2019.10  [International journal]

     View Summary

    Network analysis was used to examine how densely interconnected individual negative symptom domains are, whether some domains are more central than others, and whether sex influenced network structure. Participants included outpatients with schizophrenia (SZ; n = 201), a bipolar disorder (BD; n = 46) clinical comparison group, and healthy controls (CN; n = 27) who were rated on the Brief Negative Symptom Scale. The mutual information measure was used to construct negative symptom networks. Groups were compared on macroscopic network properties to evaluate overall network connectedness, and microscopic properties to determine which domains were most central. Macroscopic analyses indicated that patients with SZ had a less densely connected negative symptom network than BD or CN groups, and that males with SZ had less densely connected networks than females. Microscopic analyses indicated that alogia and avolition were most central in the SZ group, whereas anhedonia was most central in BD and CN groups. In addition, blunted affect, alogia, and asociality were most central in females with SZ, and alogia and avolition were most central in males with SZ. These findings suggest that negative symptoms may be highly treatment resistant in SZ because they are not very densely connected. Less densely connected networks may make treatments less likely to achieve global reductions in negative symptoms because individual domains function in isolation with little interaction. Sex differences in centralities suggest that the search for pathophysiological mechanisms and targeted treatment development should be focused on different sets of symptoms in males and females.

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  • Network Analysis Reveals the Latent Structure of Negative Symptoms in Schizophrenia.

    Gregory P Strauss, Farnaz Zamani Esfahlani, Silvana Galderisi, Armida Mucci, Alessandro Rossi, Paola Bucci, Paola Rocca, Mario Maj, Brian Kirkpatrick, Ivan Ruiz, Hiroki Sayama

    Schizophrenia bulletin   45 ( 5 ) 1033 - 1041  2019.09  [International journal]

     View Summary

    Prior studies using exploratory factor analysis provide evidence that negative symptoms are best conceptualized as 2 dimensions reflecting diminished motivation and expression. However, the 2-dimensional model has yet to be evaluated using more complex mathematical techniques capable of testing structure. In the current study, network analysis was applied to evaluate the latent structure of negative symptoms using a community-detection algorithm. Two studies were conducted that included outpatients with schizophrenia (SZ; Study 1: n = 201; Study 2: n = 912) who were rated on the Brief Negative Symptom Scale (BNSS). In both studies, network analysis indicated that the 13 BNSS items divided into 6 negative symptom domains consisting of anhedonia, avolition, asociality, blunted affect, alogia, and lack of normal distress. Separation of these domains was statistically significant with reference to a null model of randomized networks. There has been a recent trend toward conceptualizing the latent structure of negative symptoms in relation to 2 distinct dimensions reflecting diminished expression and motivation. However, the current results obtained using network analysis suggest that the 2-dimensional conceptualization is not complex enough to capture the nature of the negative symptom construct. Similar to recent confirmatory factor analysis studies, network analysis revealed that the latent structure of negative symptom is best conceptualized in relation to the 5 domains identified in the 2005 National Institute of Mental Health consensus development conference (anhedonia, avolition, asociality, blunted affect, and alogia) and potentially a sixth domain consisting of lack of normal distress. Findings have implications for identifying pathophysiological mechanisms and targeted treatments.

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  • Editorial Introduction to the Northeast Journal of Complex Systems (NEJCS)

    Hiroki Sayama, Georgi Georgiev

    Northeast Journal of Complex Systems    2019.09

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  • Diversity and Social Network Structure in Collective Decision Making: Evolutionary Perspectives with Agent-Based Simulations

    Shelley D. Dionne, Hiroki Sayama, Francis J. Yammarino

    Complexity   2019   7591072 - 16  2019.03

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  • Mathematically Modeling Emotion Regulation Abnormalities During Psychotic Experiences in Schizophrenia

    Gregory P. Strauss, Farnaz Zamani Esfahlani, Katherine Frost Visser, Elizabeth K. Dickinson, June Gruber, Hiroki Sayama

    CLINICAL PSYCHOLOGICAL SCIENCE   7 ( 2 ) 216 - 233  2019.03

     View Summary

    Ecological momentary assessment (EMA) was used to examine emotional reactivity and regulation abnormalities during the presence and absence of psychosis. Participants included 28 outpatients with schizophrenia or schizoaffective disorder (SZ) who completed 6 days of EMA. Mathematical models were applied to the EMA data to evaluate stochastic dynamic changes in emotional state and determine how the presence of psychosis influenced the interaction between emotional reactivity and regulation processes across time. Markov chain analysis indicated that although SZ tried to implement emotion regulation strategies frequently during psychotic experiences, those attempts were ineffective at reducing negative emotion from one time point to the next. Network analysis indicated that patients who were less effective at regulating their emotions during psychotic experiences had more dense connections among individual emotions. Findings indicate that psychotic experiences are associated with abnormally strong connections among discrete emotional states that are difficult to regulate despite efforts to do so.

    DOI

    Scopus

    30
    Citation
    (Scopus)
  • Cardinality Leap for Open-Ended Evolution: Theoretical Consideration and Demonstration by Hash Chemistry.

    Hiroki Sayama

    Artificial life   25 ( 2 ) 104 - 116  2019  [Refereed]  [International journal]

     View Summary

    Open-ended evolution requires unbounded possibilities that evolving entities can explore. The cardinality of a set of those possibilities thus has a significant implication for the open-endedness of evolution. I propose that facilitating formation of higher-order entities is a generalizable, effective way to cause a cardinality leap in the set of possibilities that promotes open-endedness. I demonstrate this idea with a simple, proof-of-concept toy model called Hash Chemistry that uses a hash function as a fitness evaluator of evolving entities of any size or order. Simulation results showed that the cumulative number of unique replicating entities that appeared in evolution increased almost linearly along time without an apparent bound, demonstrating the effectiveness of the proposed cardinality leap. It was also observed that the number of individual entities involved in a single replication event gradually increased over time, indicating evolutionary appearance of higher-order entities. Moreover, these behaviors were not observed in control experiments in which fitness evaluators were replaced by random number generators. This strongly suggests that the dynamics observed in Hash Chemistry were indeed evolutionary behaviors driven by selection and adaptation taking place at multiple scales.

    DOI PubMed

    Scopus

    7
    Citation
    (Scopus)
  • Capturing the Production of the Innovative Ideas: An Online Social Network Experiment and "Idea Geography" Visualization.

    Yiding Cao, Yingjun Dong, Minjun Kim, Neil G. MacLaren, Ankita Kulkarni, Shelley D. Dionne, Francis J. Yammarino, Hiroki Sayama

    CoRR   abs/1911.06353   341 - 354  2019

     View Summary

    Collective design and innovation are crucial in organizations. To investigate how the collective design and innovation processes would be affected by the diversity of knowledge and background of collective individual members, we conducted three collaborative design task experiments which involved nearly 300 participants who worked together anonymously in a social network structure using a custom-made computer-mediated collaboration platform. We compared the idea generation activity among three different background distribution conditions (clustered, random, and dispersed) with the help of the “doc2vec” text representation machine learning algorithm. We also developed a new method called “Idea Geography” to visualize the idea utility terrain on a 2D problem domain. The results showed that groups with random background allocation tended to produce the best design idea with the highest utility values. It was also suggested that the diversity of participants’ backgrounds distribution on the network might interact with each other to affect the diversity of ideas generated. The proposed idea geography successfully visualized that the collective design processes did find the high utility area through exploration and exploitation in collaborative work.

    DOI

    Scopus

    2
    Citation
    (Scopus)
  • Self-Organization and Artificial Life.

    Carlos Gershenson, Vito Trianni, Justin Werfel, Hiroki Sayama

    CoRR   abs/1903.07456  2019

  • Mutual-Information-based Feature Selection for Facial Emotion Recognition on Light-Weight Devices.

    Yingjun Dong, Hiroki Sayama

    IEEE Symposium Series on Computational Intelligence(SSCI)     2455 - 2461  2019

    DOI

    Scopus

    1
    Citation
    (Scopus)
  • Instability of Multilayer Networks Induced by Inter-Layer Coupling.

    Hyobin Kim, Farnaz Zamani Esfahlani, Samuel Heiserman, Nasim Nezamoddini, Hiroki Sayama

    IEEE Symposium Series on Computational Intelligence(SSCI)     278 - 283  2019

    DOI

    Scopus

    1
    Citation
    (Scopus)
  • Evolved Open-Endedness, Not Open-Ended Evolution.

    Howard H Pattee, Hiroki Sayama

    Artificial life   25 ( 1 ) 4 - 8  2019  [International journal]

     View Summary

    Open-endedness is often considered a prerequisite property of the whole evolutionary system and its dynamical behaviors. In the actual history of evolution on Earth, however, there are many examples showing that open-endedness is rather a consequence of evolution. We suggest that this view, which we call evolved open-endedness (EOE), be incorporated more into research on open-ended evolution. This view should allow for systematic investigation of more nuanced, more concrete research questions about open-endedness and its relationship with adaptation and sustainability.

    DOI PubMed

    Scopus

    9
    Citation
    (Scopus)
  • An Interview-Based Study of Pioneering Experiences in Teaching and Learning Complex Systems in Higher Education

    Joseph T. Lizier, Michael S. Harré, Melanie Mitchell, Simon DeDeo, Conor Finn, Kristian Lindgren, Amanda L. Lizier, Hiroki Sayama

    Complexity   2018   7306871 - 11  2018.11

    DOI

    Scopus

    5
    Citation
    (Scopus)
  • A network-based classification framework for predicting treatment response of schizophrenia patients

    Farnaz Zamani Esfahlani, Katherine Visser, Gregory P. Strauss, Hiroki Sayama

    Expert Systems with Applications   109   152 - 161  2018.11  [Refereed]

    DOI

    Scopus

    18
    Citation
    (Scopus)
  • An ecological momentary assessment evaluation of emotion regulation abnormalities in schizophrenia.

    Katherine Frost Visser, Farnaz Zamani Esfahlani, Hiroki Sayama, Gregory P Strauss

    Psychological medicine   48 ( 14 ) 2337 - 2345  2018.10  [Refereed]  [International journal]

     View Summary

    BACKGROUND: Prior studies using self-report questionnaires and laboratory-based methods suggest that schizophrenia is characterized by abnormalities in emotion regulation (i.e. using strategies to increase or decrease the frequency, duration, or intensity of negative emotion). However, it is unclear whether these abnormalities reflect poor emotion regulation effort or adequate effort, but limited effectiveness. It is also unclear whether dysfunction results primarily from one of the three stages of the emotion regulation process: identification, selection, or implementation. METHOD: The current study used ecological momentary assessment (EMA) to address these questions in the context of everyday activities. Participants included 28 outpatients diagnosed with schizophrenia (SZ) and 28 demographically matched healthy controls (CN) who completed 6 days of EMA reports of in-the-moment emotional experience, emotion regulation strategy use, and context. RESULTS: Results indicated that SZ demonstrated adequate emotion regulation effort, but poor effectiveness. Abnormalities were observed at each of the three stages of the emotion regulation process. At the identification stage, SZ initiated emotion regulation efforts at a lower threshold of negative emotion intensity. At the selection stage, SZ selected more strategies than CN and strategies attempted were less contextually appropriate. At the implementation stage, moderate to high levels of effort were ineffective at decreasing negative emotion. CONCLUSIONS: Findings suggest that although SZ attempt to control their emotions using various strategies, often applying more effort than CN, these efforts are unsuccessful; emotion regulation abnormalities may result from difficulties at the identification, selection, and implementation stages.

    DOI PubMed

    Scopus

    51
    Citation
    (Scopus)
  • How mutation alters the evolutionary dynamics of cooperation on networks

    Genki Ichinose, Yoshiki Satotani, Hiroki Sayama

    New Journal of Physics   20 ( 5 )  2018.05  [Refereed]

     View Summary

    Cooperation is ubiquitous at every level of living organisms. It is known that spatial (network) structure is a viable mechanism for cooperation to evolve. A recently proposed numerical metric, average gradient of selection (AGoS), a useful tool for interpreting and visualizing evolutionary dynamics on networks, allows simulation results to be visualized on a one-dimensional phase space. However, stochastic mutation of strategies was not considered in the analysis of AGoS. Here we extend AGoS so that it can analyze the evolution of cooperation where mutation may alter strategies of individuals on networks. We show that our extended AGoS correctly visualizes the final states of cooperation with mutation in the individual-based simulations. Our analyses revealed that mutation always has a negative effect on the evolution of cooperation regardless of the payoff functions, fraction of cooperators, and network structures. Moreover, we found that scale-free networks are the most vulnerable to mutation and thus the dynamics of cooperation are altered from bistability to coexistence on those networks, undergoing an imperfect pitchfork bifurcation.

    DOI

    Scopus

    15
    Citation
    (Scopus)
  • Seeking Open-Ended Evolution in Swarm Chemistry II: Analyzing Long-Term Dynamics via Automated Object Harvesting.

    Hiroki Sayama

    CoRR   abs/1804.03304  2018  [Refereed]

     View Summary

    We studied the long-term dynamics of evolutionary Swarm Chemistry by
    extending the simulation length ten-fold compared to earlier work and by
    developing and using a new automated object harvesting method. Both macroscopic
    dynamics and microscopic object features were characterized and tracked using
    several measures. Results showed that the evolutionary dynamics tended to
    settle down into a stable state after the initial transient period, and that
    the extent of environmental perturbations also affected the evolutionary trends
    substantially. In the meantime, the automated harvesting method successfully
    produced a huge collection of spontaneously evolved objects, revealing the
    system's autonomous creativity at an unprecedented scale.

  • How Criticality of Gene Regulatory Networks Affects the Resulting Morphogenesis under Genetic Perturbations.

    Hyobin Kim, Hiroki Sayama

    Artificial life   24 ( 2 ) 85 - 105  2018  [Refereed]  [International journal]

     View Summary

    Whereas the relationship between criticality of gene regulatory networks (GRNs) and dynamics of GRNs at a single-cell level has been vigorously studied, the relationship between the criticality of GRNs and system properties at a higher level has not been fully explored. Here we aim at revealing a potential role of criticality of GRNs in morphogenesis, which is hard to uncover through the single-cell-level studies, especially from an evolutionary viewpoint. Our model simulated the growth of a cell population from a single seed cell. All the cells were assumed to have identical intracellular GRNs. We induced genetic perturbations to the GRN of the seed cell by adding, deleting, or switching a regulatory link between a pair of genes. From numerical simulations, we found that the criticality of GRNs facilitated the formation of nontrivial morphologies when the GRNs were critical in the presence of the evolutionary perturbations. Moreover, the criticality of GRNs produced topologically homogeneous cell clusters by adjusting the spatial arrangements of cells, which led to the formation of nontrivial morphogenetic patterns. Our findings correspond to an epigenetic viewpoint that heterogeneous and complex features emerge from homogeneous and less complex components through the interactions among them. Thus, our results imply that highly structured tissues or organs in morphogenesis of multicellular organisms might stem from the criticality of GRNs.

    DOI PubMed

    Scopus

    7
    Citation
    (Scopus)
  • Graph product multilayer networks: spectral properties and applications.

    Hiroki Sayama

    J. Complex Networks   6 ( 3 ) 430 - 447  2018  [Refereed]

     View Summary

    This paper aims to establish theoretical foundations of graph product
    multilayer networks (GPMNs), a family of multilayer networks that can be
    obtained as a graph product of two or more factor networks. Cartesian, direct
    (tensor), and strong product operators are considered, and then generalized. We
    first describe mathematical relationships between GPMNs and their factor
    networks regarding their degree/strength, adjacency, and Laplacian spectra, and
    then show that those relationships can still hold for nonsimple and generalized
    GPMNs. Applications of GPMNs are discussed in three areas: predicting epidemic
    thresholds, modeling propagation in nontrivial space and time, and analyzing
    higher-order properties of self-similar networks. Directions of future research
    are also discussed.

    DOI

    Scopus

    4
    Citation
    (Scopus)
  • Complexity, Development, and Evolution in Morphogenetic Collective Systems.

    Hiroki Sayama

    CoRR   abs/1801.02086  2018  [Refereed]

     View Summary

    Many living and non-living complex systems can be modeled and understood as
    collective systems made of heterogeneous components that self-organize and
    generate nontrivial morphological structures and behaviors. This chapter
    presents a brief overview of our recent effort that investigated various
    aspects of such morphogenetic collective systems. We first propose a
    theoretical classification scheme that distinguishes four complexity levels of
    morphogenetic collective systems based on the nature of their components and
    interactions. We conducted a series of computational experiments using a
    self-propelled particle swarm model to investigate the effects of (1)
    heterogeneity of components, (2) differentiation/re-differentiation of
    components, and (3) local information sharing among components, on the
    self-organization of a collective system. Results showed that (a) heterogeneity
    of components had a strong impact on the system's structure and behavior, (b)
    dynamic differentiation/re-differentiation of components and local information
    sharing helped the system maintain spatially adjacent, coherent organization,
    (c) dynamic differentiation/re-differentiation contributed to the development
    of more diverse structures and behaviors, and (d) stochastic re-differentiation
    of components naturally realized a self-repair capability of self-organizing
    morphologies. We also explored evolutionary methods to design novel
    self-organizing patterns, using interactive evolutionary computation and
    spontaneous evolution within an artificial ecosystem. These self-organizing
    patterns were found to be remarkably robust against dimensional changes from 2D
    to 3D, although evolution worked efficiently only in 2D settings.

  • ALife and Society: Editorial Introduction to the Artificial Life Conference 2016 Special Issue.

    Jesús M Siqueiros-García, Tom Froese, Carlos Gershenson, Wendy Aguilar, Hiroki Sayama, Eduardo Izquierdo

    Artificial life   24 ( 1 ) 1 - 4  2018  [Refereed]  [International journal]

    DOI PubMed

    Scopus

  • 7
    Citation
    (Scopus)
  • Self-Organization and Artificial Life: A Review.

    Carlos Gershenson, Vito Trianni, Justin Werfel, Hiroki Sayama

    CoRR   abs/1804.01144  2018

     View Summary

    Self-organization has been an important concept within a number of
    disciplines, which Artificial Life (ALife) also has heavily utilized since its
    inception. The term and its implications, however, are often confusing or
    misinterpreted. In this work, we provide a mini-review of self-organization and
    its relationship with ALife, aiming at initiating discussions on this important
    topic with the interested audience. We first articulate some fundamental
    aspects of self-organization, outline its usage, and review its applications to
    ALife within its soft, hard, and wet domains. We also provide perspectives for
    further research.

  • Sensitivity of the Positive and Negative Syndrome Scale (PANSS) in Detecting Treatment Effects via Network Analysis.

    Farnaz Zamani Esfahlani, Hiroki Sayama, Katherine Frost Visser, Gregory P Strauss

    Innovations in clinical neuroscience   14 ( 11-12 ) 59 - 67  2017.12  [Refereed]  [International journal]

     View Summary

    Objective: The Positive and Negative Syndrome Scale is a primary outcome measure in clinical trials examining the efficacy of antipsychotic medications. Although the Positive and Negative Syndrome Scale has demonstrated sensitivity as a measure of treatment change in studies using traditional univariate statistical approaches, its sensitivity to detecting network-level changes in dynamic relationships among symptoms has yet to be demonstrated using more sophisticated multivariate analyses. In the current study, we examined the sensitivity of the Positive and Negative Syndrome Scale to detecting antipsychotic treatment effects as revealed through network analysis. Design: Participants included 1,049 individuals diagnosed with psychotic disorders from the Phase I portion of the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) study. Of these participants, 733 were clinically determined to be treatment-responsive and 316 were found to be treatment-resistant. Item level data from the Positive and Negative Syndrome Scale were submitted to network analysis, and macroscopic, mesoscopic, and microscopic network properties were evaluated for the treatment-responsive and treatment-resistant groups at baseline and post-phase I antipsychotic treatment. Results: Network analysis indicated that treatment-responsive patients had more densely connected symptom networks after antipsychotic treatment than did treatment-responsive patients at baseline, and that symptom centralities increased following treatment. In contrast, symptom networks of treatment-resistant patients behaved more randomly before and after treatment. Conclusions: These results suggest that the Positive and Negative Syndrome Scale is sensitive to detecting treatment effects as revealed through network analysis. Its findings also provide compelling new evidence that strongly interconnected symptom networks confer an overall greater probability of treatment responsiveness in patients with psychosis, suggesting that antipsychotics achieve their effect by enhancing a number of central symptoms, which then facilitate reduction of other highly coupled symptoms in a network-like fashion.

    PubMed

  • Numerical analysis on delay time and wavelength increase of inverse multiplexing using parallel routes in upgrade scenario of optical path networks

    Katsumi Takano, Hiroki Sayama

    MICROSYSTEM TECHNOLOGIES-MICRO-AND NANOSYSTEMS-INFORMATION STORAGE AND PROCESSING SYSTEMS   23 ( 5 ) 1153 - 1160  2017.05

     View Summary

    Optical inverse multiplexing is a promising technology for high-rate data transmission and rapidly increased demand for capacity. To realize this technology, a key issue is the buffering to alleviate the delay among parallel routes. As described in this paper, delay time characteristics and wavelength increase of optical inverse multiplexing using optical parallel routes in WDM mesh networks are evaluated quantitatively for rapid capacity demand, comparison with the case of whether the existing route is still used or not.

    DOI

  • TRYING BUT NOT SUCCEEDING: AN ECOLOGICAL MOMENTARY ASSESSMENT EVALUATION OF EMOTION REGULATION IN SCHIZOPHRENIA

    Katherine Visser, Farnaz Zamani Esfahlani, Hiroki Sayama, Gregory Strauss

    SCHIZOPHRENIA BULLETIN   43   S200 - S200  2017.03  [Refereed]

  • MODELING ANHEDONIA IN SCHIZOPHRENIA: A STOCHASTIC DYNAMICAL SYSTEMS APPROACH

    Gregory Strauss, Hiroki Sayama, Farnaz Zamani Esfahlani, Katherine Visser

    SCHIZOPHRENIA BULLETIN   43   S99 - S99  2017.03

  • Graph Product Multilayer Networks: Spectral Properties and Applications

    Sayama, Hiroki

    arxiv.org   abs/1701.01110   https - arxiv  2017  [Refereed]

  • Robust tracking and behavioral modeling of movements of biological collectives from ordinary video recordings.

    Hiroki Sayama, Farnaz Zamani Esfahlani, Ali Jazayeri, J. Scott Turner

    2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017 - Proceedings   2018-   1 - 8  2017  [Refereed]

     View Summary

    We propose a novel computational method to extract information about
    interactions among individuals with different behavioral states in a biological
    collective from ordinary video recordings. Assuming that individuals are acting
    as finite state machines, our method first detects discrete behavioral states
    of those individuals and then constructs a model of their state transitions,
    taking into account the positions and states of other individuals in the
    vicinity. We have tested the proposed method through applications to two
    real-world biological collectives: termites in an experimental setting and
    human pedestrians in a university campus. For each application, a robust
    tracking system was developed in-house, utilizing interactive human
    intervention (for termite tracking) or online agent-based simulation (for
    pedestrian tracking). In both cases, significant interactions were detected
    between nearby individuals with different states, demonstrating the
    effectiveness of the proposed method.

    DOI

  • Predicting stock market movements using network science: an information theoretic approach.

    Minjun Kim, Hiroki Sayama

    Applied network science   2 ( 1 ) 35 - 35  2017  [Refereed]  [International journal]

     View Summary

    A stock market is considered as one of the highly complex systems, which consists of many components whose prices move up and down without having a clear pattern. The complex nature of a stock market challenges us on making a reliable prediction of its future movements. In this paper, we aim at building a new method to forecast the future movements of Standard & Poor's 500 Index (S&P 500) by constructing time-series complex networks of S&P 500 underlying companies by connecting them with links whose weights are given by the mutual information of 60-min price movements of the pairs of the companies with the consecutive 5340 min price records. We showed that the changes in the strength distributions of the networks provide an important information on the network's future movements. We built several metrics using the strength distributions and network measurements such as centrality, and we combined the best two predictors by performing a linear combination. We found that the combined predictor and the changes in S&P 500 show a quadratic relationship, and it allows us to predict the amplitude of the one step future change in S&P 500. The result showed significant fluctuations in S&P 500 Index when the combined predictor was high. In terms of making the actual index predictions, we built ARIMA models with and without inclusion of network measurements, and compared the predictive power of them. We found that adding the network measurements into the ARIMA models improves the model accuracy. These findings are useful for financial market policy makers as an indicator based on which they can interfere with the markets before the markets make a drastic change, and for quantitative investors to improve their forecasting models.

    DOI PubMed

    Scopus

    18
    Citation
    (Scopus)
  • NetSciEd: Network Science and Education for the Interconnected World.

    Hiroki Sayama, Catherine Cramer, Lori Sheetz, Stephen M. Uzzo

    CoRR   abs/1706.00115 ( 2 ) 104 - 115  2017  [Refereed]

     View Summary

    This short article presents a summary of the NetSciEd (Network Science and
    Education) initiative that aims to address the need for curricula, resources,
    accessible materials, and tools for introducing K-12 students and the general
    public to the concept of networks, a crucial framework in understanding
    complexity. NetSciEd activities include (1) the NetSci High educational
    outreach program (since 2010), which connects high school students and their
    teachers with regional university research labs and provides them with the
    opportunity to work on network science research projects; (2) the NetSciEd
    symposium series (since 2012), which brings network science researchers and
    educators together to discuss how network science can help and be integrated
    into formal and informal education; and (3) the Network Literacy: Essential
    Concepts and Core Ideas booklet (since 2014), which was created collaboratively
    and subsequently translated into 18 languages by an extensive group of network
    science researchers and educators worldwide.

  • Mapping the Curricular Structure and Contents of Network Science Courses.

    Hiroki Sayama

    CoRR   abs/1707.09570  2017  [Refereed]

  • Invasion of Cooperation in Scale-Free Networks: Accumulated versus Average Payoffs

    Ichinose, Genki, Sayama, Hiroki

    Artificial Life   23 ( 1 ) 25 - 33  2017  [Refereed]  [International journal]

     View Summary

    It is well known that cooperation cannot be an evolutionarily stable strategy for a non-iterative game in a well-mixed population. In contrast, structured populations favor cooperation, since cooperators can benefit each other by forming local clusters. Previous studies have shown that scale-free networks strongly promote cooperation. However, little is known about the invasion mechanism of cooperation in scale-free networks. To study microscopic and macroscopic behaviors of cooperators' invasion, we conducted computational experiments on the evolution of cooperation in scale-free networks where, starting from all defectors, cooperators can spontaneously emerge by mutation. Since the evolutionary dynamics are influenced by the definition of fitness, we tested two commonly adopted fitness functions: accumulated payoff and average payoff. Simulation results show that cooperation is strongly enhanced with the accumulated payoff fitness compared to the average payoff fitness. However, the difference between the two functions decreases as the average degree increases. As the average degree increases, cooperation decreases for the accumulated payoff fitness, while it increases for the average payoff fitness. Moreover, for the average payoff fitness, low-degree nodes play a more important role in spreading cooperative strategies than for the accumulated payoff fitness.

    DOI PubMed

    Scopus

    26
    Citation
    (Scopus)
  • How mutation alters fitness of cooperation in networked evolutionary games.

    Genki Ichinose, Yoshiki Satotani, Hiroki Sayama

    Proceedings of the Fourteenth European Conference Artificial Life, ECAL 2017, Lyon, France, September 4-8, 2017     208 - 213  2017  [Refereed]

     View Summary

    Cooperation is ubiquitous in every level of living organisms. It is known
    that spatial (network) structure is a viable mechanism for cooperation to
    evolve. Until recently, it has been difficult to predict whether cooperation
    can evolve at a network (population) level. To address this problem, Pinheiro
    et al. proposed a numerical metric, called Average Gradient of Selection (AGoS)
    in 2012. AGoS can characterize and forecast the evolutionary fate of
    cooperation at a population level. However, stochastic mutation of strategies
    was not considered in the analysis of AGoS. Here we analyzed the evolution of
    cooperation using AGoS where mutation may occur to strategies of individuals in
    networks. Our analyses revealed that mutation always has a negative effect on
    the evolution of cooperation regardless of the fraction of cooperators and
    network structures. Moreover, we found that mutation affects the fitness of
    cooperation differently on different social network structures.

    DOI

  • Criticality of gene regulatory networks and the resulting morphogenesis.

    Hyobin Kim, Hiroki Sayama

    Proceedings of the Fourteenth European Conference Artificial Life, ECAL 2017, Lyon, France, September 4-8, 2017     245 - 246  2017  [Refereed]

    DOI

  • Combinatorial Miller-Hagberg Algorithm for Randomization of Dense Networks.

    Hiroki Sayama

    CoRR   abs/1710.02733  2017  [Refereed]

     View Summary

    We propose a slightly revised Miller-Hagberg (MH) algorithm that efficiently
    generates a random network from a given expected degree sequence. The revision
    was to replace the approximated edge probability between a pair of nodes with a
    combinatorically calculated edge probability that better captures the
    likelihood of edge presence especially where edges are dense. The computational
    complexity of this combinatorial MH algorithm is still in the same order as the
    original one. We evaluated the proposed algorithm through several numerical
    experiments. The results demonstrated that the proposed algorithm was
    particularly good at accurately representing high-degree nodes in dense,
    heterogeneous networks. This algorithm may be a useful alternative of other
    more established network randomization methods, given that the data are
    increasingly becoming larger and denser in today's network science research.

  • Robust Tracking and Behavioral Modeling of Movements of Biological Collectives from Ordinary Video Recordings.

    Hiroki Sayama, Farnaz Zamani Esfahlani, Ali Jazayeri, J. Scott Turner

    CoRR   abs/1707.07310   1 - 8  2017

    DOI

  • Predicting stock market movements using network science: An information theoretic approach.

    Minjun Kim, Hiroki Sayama

    CoRR   abs/1705.07980   35 - 35  2017

    DOI

    Scopus

    18
    Citation
    (Scopus)
  • Special Issue on Morphogenetic Engineering

    Rene Doursat, Hiroki Sayama

    IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS   8 ( 4 ) 310 - 311  2016.12  [Refereed]

    DOI

    Scopus

  • The Ebola Crisis and the Corresponding Public Behavior: A System Dynamics Approach.

    Nasser Sharareh, Nasim S Sabounchi, Hiroki Sayama, Roderick MacDonald

    PLoS currents   8  2016.11  [Refereed]  [International journal]

     View Summary

    BACKGROUND: The interaction of several sociocultural and environmental factors during an epidemic crisis leads to behavioral responses that consequently make the crisis control a complex problem. METHODS: The system dynamics approach has been adopted to study the relationships between spread of disease, public attention, situational awareness, and community's response to the Ebola epidemic. RESULTS: In developing different simulation models to capture the trend of death and incidence data from the World Health Organization for the Ebola outbreak, the final model has the best fit to the historical trends. Results demonstrate that the increase of quarantining rate over time due to increase in situational awareness and performing safe burials had a significant impact on the control of epidemic. However, public attention did not play a significant role. CONCLUSION: The best fit to historical data are achieved when behavioral factors specific to West Africa like studying the Situational Awareness and Public Attention are included in the model. However, by ignoring the sociocultural factors, the model is not able to represent the reality; therefore, in the case of any epidemics, it is necessary that all the parties and community members find the most significant behavioral factors that can curb the epidemic.

    DOI PubMed

  • Brain response pattern identification of fMRI data using a particle swarm optimization-based approach.

    Xinpei Ma, Chun-An Chou, Hiroki Sayama, Wanpracha Art Chaovalitwongse

    Brain informatics   3 ( 3 ) 181 - 192  2016.09  [Refereed]  [International journal]

     View Summary

    Many neuroscience studies have been devoted to understand brain neural responses correlating to cognition using functional magnetic resonance imaging (fMRI). In contrast to univariate analysis to identify response patterns, it is shown that multi-voxel pattern analysis (MVPA) of fMRI data becomes a relatively effective approach using machine learning techniques in the recent literature. MVPA can be considered as a multi-objective pattern classification problem with the aim to optimize response patterns, in which informative voxels interacting with each other are selected, achieving high classification accuracy associated with cognitive stimulus conditions. To solve the problem, we propose a feature interaction detection framework, integrating hierarchical heterogeneous particle swarm optimization and support vector machines, for voxel selection in MVPA. In the proposed approach, we first select the most informative voxels and then identify a response pattern based on the connectivity of the selected voxels. The effectiveness of the proposed approach was examined for the Haxby's dataset of object-level representations. The computational results demonstrated higher classification accuracy by the extracted response patterns, compared to state-of-the-art feature selection algorithms, such as forward selection and backward selection.

    DOI PubMed

    Scopus

    15
    Citation
    (Scopus)
  • Estimation of Laplacian spectra of direct and strong product graphs

    Hiroki Sayama

    Discrete Applied Mathematics   205   160 - 170  2016.05  [Refereed]

     View Summary

    Calculating a product of multiple graphs has been studied in mathematics, engineering, computer science, and more recently in network science, particularly in the context of multilayer networks. One of the important questions to be addressed in this area is how to characterize spectral properties of a product graph using those of its factor graphs. While several such characterizations have already been obtained analytically (mostly for adjacency spectra), characterization of Laplacian spectra of direct product and strong product graphs has remained an open problem. Here we develop practical methods to estimate Laplacian spectra of direct and strong product graphs from spectral properties of their factor graphs using a few heuristic assumptions. Numerical experiments showed that the proposed methods produced reasonable estimation with percentage errors confined within a 10% range for most eigenvalues. (C) 2015 Elsevier B.V. All rights reserved.

    DOI

    Scopus

    16
    Citation
    (Scopus)
  • Collective decision making, leadership, and collective intelligence: Tests with agent-based simulations and a Field study

    Kristie A. McHugh, Francis J. Yammarino, Shelley D. Dionne, Andra Serban, Hiroki Sayama, Subimal Chatterjee

    LEADERSHIP QUARTERLY   27 ( 2 ) 218 - 241  2016.04  [Refereed]

     View Summary

    This multi-level (individual and collective) study examines collective decision making as it relates to the performance metric of collective decision quality. A collectivistic leadership approach is used, as leaderless collectives engaged in decision making are inherently involved in collective leadership. A multi-level conceptual model for collective decision making is introduced, which incorporates leadership and collective intelligence. Using agent-based simulations and content-coded field study data, results from both methods suggest that there is a positive relationship between individual and collective intelligence, as well as a positive relationship between collective intelligence and collective decision quality. The implications of these and related findings for future collective level research bridging the fields of decision making, leadership, and collective intelligence are discussed. (C) 2016 Elsevier Inc. All rights reserved.

    DOI

    Scopus

    63
    Citation
    (Scopus)
  • The Ebola Crisis and the Corresponding Public Behavior: A System Dynamics Approach

    Sharareh, Nasser, Sabounchi, Nasim S, Sayama, Hiroki, MacDonald, Roderick

    PLOS Currents Outbreaks    2016  [Refereed]

  • The relationship between microscopic and collective properties in gene regulatory network-based morphogenetic systems

    Kim Hyobin, Sayama Hiroki

    Proceedings of the Artificial Life Conference 2016 (ALIFE XV)     370  2016  [Refereed]

  • Self-control of networks via adaptive link weight adjustment

    Hejazibakhsh Mahboobeh, Sayama Hiroki

    Proceedings of the 2016 SIAM Workshop on Network Science (NS 16)     84  2016  [Refereed]

  • Proceedings of the Artificial Life Conference 2016 (ALIFE XV)

    Gershenson Carlos, Froese Tom, Siqueiros Jesus M, Aguilar Wendy, Izquierdo Eduardo J, Sayama Hiroki

       2016  [Refereed]

  • Ecological Patterns of Self-Replicators

    Sayama, Hiroki

    Designing Beauty: The Art of Cellular Automata     97 - 101  2016  [Refereed]

  • Visualizing the “Heartbeat” of a City with Tweets

    Fran{\c{c } }a, Urbano, Sayama, Hiroki, McSwiggen, Colin, Daneshvar, Roozbeh, Bar-Yam, Yaneer

    Complexity   21 ( 6 ) 280 - 287  2016  [Refereed]

     View Summary

    Describing the dynamics of a city is a crucial step to both understanding the human activity in urban environments and to planning and designing cities accordingly. Here, we describe the collective dynamics of New York City (NYC) and surrounding areas as seen through the lens of Twitter usage. In particular, we observe and quantify the patterns that emerge naturally from the hourly activities in different areas of NYC, and discuss how they can be used to understand the urban areas. Using a dataset that includes more than 6 million geolocated Twitter messages we construct a movie of the geographic density of tweets. We observe the diurnal heartbeat of the NYC area. The largest scale dynamics are the waking and sleeping cycle and commuting from residential communities to office areas in Manhattan. Hourly dynamics reflect the interplay of commuting, work and leisure, including whether people are preoccupied with other activities or actively using Twitter. Differences between weekday and weekend dynamics point to changes in when people wake and sleep, and engage in social activities. We show that by measuring the average distances to a central location one can quantify the weekly differences and the shift in behavior during weekends. We also identify locations and times of high Twitter activity that occur because of specific activities. These include early morning high levels of traffic as people arrive and wait at air transportation hubs, and on Sunday at the Meadowlands Sports Complex and Statue of Liberty. We analyze the role of particular individuals where they have large impacts on overall Twitter activity. Our analysis points to the opportunity to develop insight into both geographic social dynamics and attention through social media analysis. (c) 2015 Wiley Periodicals, Inc. Complexity 21: 280-287, 2016

    DOI

    Scopus

    21
    Citation
    (Scopus)
  • 3D tactile map printing for the visually impaired in Boston

    Dixon Caitlin, Nielsen Gregory, Reardon Claire, Sayama Hiroki, Silfer Daniel, Stahovic Stephanie

    Proceedings of the Annual General Donald R. Keith Memorial Conference    2016  [Refereed]

  • Collective decision making, leadership, and collective intelligence: Tests with agent-based simulations and a Field study

    McHugh, Kristie A, Yammarino, Francis J, Dionne, Shelley D, Serban, Andra, Sayama, Hiroki, Chatterjee, Subimal

    The Leadership Quarterly   27 ( 2 ) 218 - 241  2016  [Refereed]

     View Summary

    This multi-level (individual and collective) study examines collective decision making as it relates to the performance metric of collective decision quality. A collectivistic leadership approach is used, as leaderless collectives engaged in decision making are inherently involved in collective leadership. A multi-level conceptual model for collective decision making is introduced, which incorporates leadership and collective intelligence. Using agent-based simulations and content-coded field study data, results from both methods suggest that there is a positive relationship between individual and collective intelligence, as well as a positive relationship between collective intelligence and collective decision quality. The implications of these and related findings for future collective level research bridging the fields of decision making, leadership, and collective intelligence are discussed. (C) 2016 Elsevier Inc. All rights reserved.

    DOI

    Scopus

    63
    Citation
    (Scopus)
  • Brain response pattern identification of fMRI data using a particle swarm optimization-based approach

    Ma, Xinpei, Chou, Chun-An, Sayama, Hiroki, Chaovalitwongse, Wanpracha Art

    Brain Informatics     1 - 12  2016  [Refereed]

  • Chapitre 18. L’ingénierie morphogénétique: modèles de processus dynamiques pour la morphogenèse

    Doursat, Ren{\'e}, Sayama, Hiroki, Michel, Olivier

    Modélisations, simulations, systèmes complexes     625 - 642  2016  [Refereed]

  • A state equation for the Schelling’s segregation model

    Shin, Jae Kyun, Sayama, Hiroki, Choi, Seung Ryul

    Complex & Intelligent Systems   2 ( 1 ) 35 - 43  2016  [Refereed]

  • What are essential concepts about networks?

    Hiroki Sayama, Catherine Cramer, Mason A. Porter, Lori Sheetz, Stephen M. Uzzo

    J. Complex Networks   4 ( 3 ) 457 - 474  2016  [Refereed]

     View Summary

    Networks have become increasingly relevant to everyday life as human society
    has become increasingly connected. Attaining a basic understanding of networks
    has thus become a necessary form of literacy for people (and for youths in
    particular). At the NetSci 2014 conference, we initiated a year-long process to
    develop an educational resource that concisely summarizes essential concepts
    about networks that can be used by anyone of school age or older. The process
    involved several brainstorming sessions on one key question: "What should every
    person living in the 21st century know about networks by the time he/she
    finishes secondary education?" Different sessions reached diverse participants,
    which included professional researchers in network science, educators, and
    high-school students. The generated ideas were connected by the students to
    construct a concept network. We examined community structure in the concept
    network to group ideas into a set of important themes, which we refined through
    discussion into seven essential concepts. The students played a major role in
    this development process by providing insights and perspectives that were often
    unrecognized by researchers and educators. The final result, "Network Literacy:
    Essential Concepts and Core Ideas", is now available as a booklet in several
    different languages from http://tinyurl.com/networkliteracy .

    DOI

    Scopus

    9
    Citation
    (Scopus)
  • Visualizing the "heartbeat" of a city with tweets.

    Urbano França, Hiroki Sayama, Colin McSwiggen, Roozbeh Daneshvar, Yaneer Bar-Yam

    Complex.   21 ( 6 ) 280 - 287  2016  [Refereed]

     View Summary

    Describing the dynamics of a city is a crucial step to both understanding the human activity in urban environments and to planning and designing cities accordingly. Here, we describe the collective dynamics of New York City (NYC) and surrounding areas as seen through the lens of Twitter usage. In particular, we observe and quantify the patterns that emerge naturally from the hourly activities in different areas of NYC, and discuss how they can be used to understand the urban areas. Using a dataset that includes more than 6 million geolocated Twitter messages we construct a movie of the geographic density of tweets. We observe the diurnal heartbeat of the NYC area. The largest scale dynamics are the waking and sleeping cycle and commuting from residential communities to office areas in Manhattan. Hourly dynamics reflect the interplay of commuting, work and leisure, including whether people are preoccupied with other activities or actively using Twitter. Differences between weekday and weekend dynamics point to changes in when people wake and sleep, and engage in social activities. We show that by measuring the average distances to a central location one can quantify the weekly differences and the shift in behavior during weekends. We also identify locations and times of high Twitter activity that occur because of specific activities. These include early morning high levels of traffic as people arrive and wait at air transportation hubs, and on Sunday at the Meadowlands Sports Complex and Statue of Liberty. We analyze the role of particular individuals where they have large impacts on overall Twitter activity. Our analysis points to the opportunity to develop insight into both geographic social dynamics and attention through social media analysis. (c) 2015 Wiley Periodicals, Inc. Complexity 21: 280-287, 2016

    DOI

    Scopus

    21
    Citation
    (Scopus)
  • Hierarchical heterogeneous particle swarm optimization: algorithms and evaluations.

    Xinpei Ma, Hiroki Sayama

    IJPEDS   31 ( 5 ) 504 - 516  2016  [Refereed]

    DOI

    Scopus

    3
    Citation
    (Scopus)
  • Editorial Introduction to the Artificial Life 14 Conference Special Issue

    Sayama, Hiroki, Rieffel, John, Risi, Sebastian, Doursat, Ren{\'e}, Lipson, Hod

    Artificial Life   22 ( 2 ) 135 - 7  2016  [Refereed]  [International journal]

    DOI PubMed

    Scopus

  • A Polynomial-Time Deterministic Approach to the Traveling Salesperson Problem

    Jazayeri, Ali, Sayama, Hiroki

    arXiv preprint arXiv:1608.01716   abs/1608.01716  2016  [Refereed]

     View Summary

    We propose a new polynomial-time deterministic algorithm that produces an
    approximated solution for the traveling salesperson problem. The proposed
    algorithm ranks cities based on their priorities calculated using a power
    function of means and standard deviations of their distances from other cities
    and then connects the cities to their neighbors in the order of their
    priorities. When connecting a city, a neighbor is selected based on their
    neighbors' priorities calculated as another power function that additionally
    includes their distance from the focal city to be connected. This repeats until
    all the cities are connected into a single loop. The time complexity of the
    proposed algorithm is $O(n^2)$, where $n$ is the number of cities. Numerical
    evaluation shows that, despite its simplicity, the proposed algorithm produces
    shorter tours with less time complexity than other conventional tour
    construction heuristics. The proposed algorithm can be used by itself or as an
    initial tour generator for other more complex heuristic optimization
    algorithms.

  • Developmental changes in spontaneous electrocortical activity and network organization from early to late childhood.

    Vladimir Miskovic, Xinpei Ma, Chun-An Chou, Miaolin Fan, Max Owens, Hiroki Sayama, Brandon E Gibb

    NeuroImage   118   237 - 47  2015.09  [Refereed]  [International journal]

     View Summary

    We investigated the development of spontaneous (resting state) cerebral electric fields and their network organization from early to late childhood in a large community sample of children. Critically, we examined electrocortical maturation across one-year windows rather than creating aggregate averages that can miss subtle maturational trends. We implemented several novel methodological approaches including a more fine grained examination of spectral features across multiple electrodes, the use of phase-lagged functional connectivity to control for the confounding effects of volume conduction and applying topological network analyses to weighted cortical adjacency matrices. Overall, there were major decreases in absolute EEG spectral density (particularly in the slow wave range) across cortical lobes as a function of age. Moreover, the peak of the alpha frequency increased with chronological age and there was a redistribution of relative spectral density toward the higher frequency ranges, consistent with much of the previous literature. There were age differences in long range functional brain connectivity, particularly in the alpha frequency band, culminating in the most dense and spatially variable networks in the oldest children. We discovered age-related reductions in characteristic path lengths, modularity and homogeneity of alpha-band cortical networks from early to late childhood. In summary, there is evidence of large scale reorganization in endogenous brain electric fields from early to late childhood, suggesting reduced signal amplitudes in the presence of more functionally integrated and band limited coordination of neuronal activity across the cerebral cortex.

    DOI PubMed

    Scopus

    108
    Citation
    (Scopus)
  • Complexity measures and concept learning

    Andreas D. Pape, Kenneth J. Kurtz, Hiroki Sayama

    Journal of Mathematical Psychology   64-65   66 - 75  2015.02  [Refereed]

     View Summary

    The nature of concept learning is a core question in cognitive science. Theories must account for the relative difficulty of acquiring different concepts by supervised learners. For a canonical set of six category types, two distinct orderings of classification difficulty have been found. One ordering, which we call paradigm-specific, occurs when adult human learners classify objects with easily distinguishable characteristics such as size, shape, and shading. The general order occurs in all other known cases: when adult humans classify objects with characteristics that are not readily distinguished (e.g., brightness, saturation, hue); for children and monkeys; and when categorization difficulty is extrapolated from errors in identification learning. The paradigm-specific order was found to be predictable mathematically by measuring the logical complexity of tasks, i.e., how concisely the solution can be represented by logical rules.
    However, logical complexity explains only the paradigm-specific order but not the general order. Here we propose a new difficulty measurement, information complexity, that calculates the amount of uncertainty remaining when a subset of the dimensions are specified. This measurement is based on Shannon entropy. We show that, when the metric extracts minimal uncertainties, this new measurement predicts the paradigm-specific order for the canonical six category types, and when the metric extracts average uncertainties, this new measurement predicts the general order. Moreover, for learning category types beyond the canonical six, we find that the minimal-uncertainty formulation correctly predicts the paradigm-specific order as well or better than existing metrics (Boolean complexity and GIST) in most cases. (C) 2015 Elsevier Inc. All rights reserved.

    DOI

    Scopus

    6
    Citation
    (Scopus)
  • Transitions between homophilic and heterophilic modes of cooperation

    Ichinose, Genki, Saito, Masaya, Sayama, Hiroki, Bersini, Hugues

    Journal of Artificial Societies and Social Simulation   18 ( 4 ) 3 - 3  2015  [Refereed]

     View Summary

    Cooperation is ubiquitous in biological and social systems. Previous studies revealed that a preference toward similar appearance promotes cooperation, a phenomenon called tag-mediated cooperation or communitarian cooperation. This effect is enhanced when a spatial structure is incorporated, because space allows agents sharing an identical tag to regroup to form locally cooperative clusters. In spatially distributed settings, one can also consider migration of organisms, which has a potential to further promote evolution of cooperation by facilitating spatial clustering. However, it has not yet been considered in spatial tag-mediated cooperation models. Here we show, using computer simulations of a spatial model of evolutionary games with organismal migration, that tag-based segregation and homophilic cooperation arise for a wide range of parameters. In the meantime, our results also show another evolutionarily stable outcome, where a high level of heterophilic cooperation is maintained in spatially well-mixed patterns. We found that these two different forms of tag-mediated cooperation appear alternately as the parameter for temptation to defect is increased.

    DOI

    Scopus

    1
    Citation
    (Scopus)
  • What are essential concepts about networks?

    Sayama, Hiroki, Cramer, Catherine, Porter, Mason A, Sheetz, Lori, Uzzo, Stephen

    Journal of Complex Networks / arXiv preprint arXiv:1507.03490   abs/1507.03490  2015  [Refereed]

  • Hierarchical heterogeneous particle swarm optimization: algorithms and evaluations

    Ma, Xinpei, Sayama, Hiroki

    International Journal of Parallel, Emergent and Distributed Systems   31 ( 5 ) DOI - 10  2015  [Refereed]

    DOI

    Scopus

    3
    Citation
    (Scopus)
  • Estimation of Laplacian spectra of direct and strong product graphs

    Sayama, Hiroki

    Discrete Applied Mathematics   abs/1507.03030  2015  [Refereed]

     View Summary

    Calculating a product of multiple graphs has been studied in mathematics,
    engineering, computer science, and more recently in network science,
    particularly in the context of multilayer networks. One of the important
    questions to be addressed in this area is how to characterize spectral
    properties of a product graph using those of its factor graphs. While several
    such characterizations have already been obtained analytically (mostly for
    adjacency spectra), characterization of Laplacian spectra of direct product and
    strong product graphs has remained an open problem. Here we develop practical
    methods to estimate Laplacian spectra of direct and strong product graphs from
    spectral properties of their factor graphs using a few heuristic assumptions.
    Numerical experiments showed that the proposed methods produced reasonable
    estimation with percentage errors confined within a +/-10% range for most
    eigenvalues.

    DOI

    Scopus

    16
    Citation
    (Scopus)
  • Developmental changes in spontaneous electrocortical activity and network organization from early to late childhood

    Miskovic, Vladimir, Ma, Xinpei, Chou, Chun-An, Fan, Miaolin, Owens, Max, Sayama, Hiroki, Gibb, Br, on E

    NeuroImage   118   237 - 247  2015  [Refereed]

     View Summary

    We investigated the development of spontaneous (resting state) cerebral electric fields and their network organization from early to late childhood in a large community sample of children. Critically, we examined electrocortical maturation across one-year windows rather than creating aggregate averages that can miss subtle maturational trends. We implemented several novel methodological approaches including a more fine grained examination of spectral features across multiple electrodes, the use of phase-lagged functional connectivity to control for the confounding effects of volume conduction and applying topological network analyses to weighted cortical adjacency matrices. Overall, there were major decreases in absolute EEG spectral density (particularly in the slow wave range) across cortical lobes as a function of age. Moreover, the peak of the alpha frequency increased with chronological age and there was a redistribution of relative spectral density toward the higher frequency ranges, consistent with much of the previous literature. There were age differences in long range functional brain connectivity, particularly in the alpha frequency band, culminating in the most dense and spatially variable networks in the oldest children. We discovered age-related reductions in characteristic path lengths, modularity and homogeneity of alpha-band cortical networks from early to late childhood. In summary, there is evidence of large scale reorganization in endogenous brain electric fields from early to late childhood, suggesting reduced signal amplitudes in the presence of more functionally integrated and band limited coordination of neuronal activity across the cerebral cortex. (C) 2015 Elsevier Inc. All rights reserved.

    DOI

    Scopus

    108
    Citation
    (Scopus)
  • Network Literacy: Essential Concepts and Core Ideas

    Cramer, Catherine, Porter, Mason, Sayama, Hiroki, Sheetz, Lori, Uzzo, Stephen

    http://tinyurl.com/networkliteracy    2015  [Refereed]

  • Complexity measures and concept learning

    Pape, Andreas D, Kurtz, Kenneth J, Sayama, Hiroki

    Journal of Mathematical Psychology   64   66 - 75  2015  [Refereed]

     View Summary

    The nature of concept learning is a core question in cognitive science. Theories must account for the relative difficulty of acquiring different concepts by supervised learners. For a canonical set of six category types, two distinct orderings of classification difficulty have been found. One ordering, which we call paradigm-specific, occurs when adult human learners classify objects with easily distinguishable characteristics such as size, shape, and shading. The general order occurs in all other known cases: when adult humans classify objects with characteristics that are not readily distinguished (e.g., brightness, saturation, hue); for children and monkeys; and when categorization difficulty is extrapolated from errors in identification learning. The paradigm-specific order was found to be predictable mathematically by measuring the logical complexity of tasks, i.e., how concisely the solution can be represented by logical rules.
    However, logical complexity explains only the paradigm-specific order but not the general order. Here we propose a new difficulty measurement, information complexity, that calculates the amount of uncertainty remaining when a subset of the dimensions are specified. This measurement is based on Shannon entropy. We show that, when the metric extracts minimal uncertainties, this new measurement predicts the paradigm-specific order for the canonical six category types, and when the metric extracts average uncertainties, this new measurement predicts the general order. Moreover, for learning category types beyond the canonical six, we find that the minimal-uncertainty formulation correctly predicts the paradigm-specific order as well or better than existing metrics (Boolean complexity and GIST) in most cases. (C) 2015 Elsevier Inc. All rights reserved.

    DOI

    Scopus

    6
    Citation
    (Scopus)
  • Mental Disorder Recovery Correlated with Centralities and Interactions on an Online Social Network

    Ma, Xinpei, Sayama, Hiroki

    PeerJ   3   e1163  2015  [Refereed]

     View Summary

    Recent research has established both a theoretical basis and strong empirical evidence that effective social behavior plays a beneficial role in the maintenance of physical and psychological well-being of people. To test whether social behavior and well-being are also associated in online communities, we studied the correlations between the recovery of patients with mental disorders and their behaviors in online social media. As the source of the data related to the social behavior and progress of mental recovery, we used PatientsLikeMe (PLM), the world's first open-participation research platformfor the development of patient-centered health outcome measures. We first constructed an online social network structure based on patient-to-patient ties among 200 patients obtained from PLM. We then characterized patients' online social activities by measuring the numbers of "posts and views" and " helpful marks" each patient obtained. The patients' recovery data were obtained from their self-reported status information that was also available on PLM. We found that some node properties (in-degree, eigenvector centrality and PageRank) and the two online social activity measures were significantly correlated with patients' recovery. Furthermore, we re-collected the patients' recovery data two months after the first data collection. We found significant correlations between the patients' social behaviors and the second recovery data, which were collected two months apart. Our results indicated that social interactions in online communities such as PLM were significantly associated with the current and future recoveries of patients with mental disorders.

    DOI

    Scopus

    9
    Citation
    (Scopus)
  • Transitions Between Homophilic and Heterophilic Modes of Cooperation.

    Genki Ichinose, Masaya Saito, Hiroki Sayama, Hugues Bersini

    J. Artif. Soc. Soc. Simul.   18 ( 4 )  2015  [Refereed]

     View Summary

    Cooperation is ubiquitous in biological and social systems. Previous studies
    revealed that a preference toward similar appearance promotes cooperation, a
    phenomenon called tag-mediated cooperation or communitarian cooperation. This
    effect is enhanced when a spatial structure is incorporated, because space
    allows agents sharing an identical tag to regroup to form locally cooperative
    clusters. In spatially distributed settings, one can also consider migration of
    organisms, which has a potential to further promote evolution of cooperation by
    facilitating spatial clustering. However, it has not yet been considered in
    spatial tag-mediated cooperation models. Here we show, using computer
    simulations of a spatial model of evolutionary games with organismal migration,
    that tag-based segregation and homophilic cooperation arise for a wide range of
    parameters. In the meantime, our results also show another evolutionarily
    stable outcome, where a high level of heterophilic cooperation is maintained in
    spatially well-mixed patterns. We found that these two different forms of
    tag-mediated cooperation appear alternately as the parameter for temptation to
    defect is increased.

    DOI

    Scopus

    1
    Citation
    (Scopus)
  • Studying Collective Human Decision Making and Creativity with Evolutionary Computation

    Sayama, Hiroki, Dionne, Shelley D

    Artificial Life   21 ( 3 ) 379 - 393  2015  [Refereed]

     View Summary

    We report a summary of our interdisciplinary research project "Evolutionary
    Perspective on Collective Decision Making" that was conducted through close
    collaboration between computational, organizational and social scientists at
    Binghamton University. We redefined collective human decision making and
    creativity as evolution of ecologies of ideas, where populations of ideas
    evolve via continual applications of evolutionary operators such as
    reproduction, recombination, mutation, selection, and migration of ideas, each
    conducted by participating humans. Based on this evolutionary perspective, we
    generated hypotheses about collective human decision making using agent-based
    computer simulations. The hypotheses were then tested through several
    experiments with real human subjects. Throughout this project, we utilized
    evolutionary computation (EC) in non-traditional ways---(1) as a theoretical
    framework for reinterpreting the dynamics of idea generation and selection, (2)
    as a computational simulation model of collective human decision making
    processes, and (3) as a research tool for collecting high-resolution
    experimental data of actual collaborative design and decision making from human
    subjects. We believe our work demonstrates untapped potential of EC for
    interdisciplinary research involving human and social dynamics.

    DOI

    Scopus

    18
    Citation
    (Scopus)
  • Social diffusion and global drift on networks

    Sayama, Hiroki, Sinatra, Roberta

    Physical Review E   91 ( 3 ) 032809 - 032809  2015  [Refereed]  [International journal]

     View Summary

    We study a mathematical model of social diffusion on a symmetric weighted network where individual nodes' states gradually assimilate to local social norms made by their neighbors' average states. Unlike physical diffusion, this process is not state conservational and thus the global state of the network (i.e., sum of node states) will drift. The asymptotic average node state will be the average of initial node states weighted by their strengths. Here we show that, while the global state is not conserved in this process, the inner product of strength and state vectors is conserved instead, and perfect positive correlation between node states and local averages of their self-neighbor strength ratios always results in upward (or at least neutral) global drift. We also show that the strength assortativity negatively affects the speed of homogenization. Based on these findings, we propose an adaptive link weight adjustment method to achieve the highest upward global drift by increasing the strength-state correlation. The effectiveness of the method was confirmed through numerical simulations and implications for real-world social applications are discussed.

    DOI PubMed

    Scopus

    3
    Citation
    (Scopus)
  • NetSci High: Bringing Network Science Research to High Schools

    Cramer, Catherine, Sheetz, Lori, Sayama, Hiroki, Trunfio, Paul, Stanley, H Eugene, Uzzo, Stephen

    Complex Networks VI   597   209 - 218  2015  [Refereed]

     View Summary

    We present NetSci High, our NSF-funded educational outreach program that
    connects high school students who are underrepresented in STEM (Science
    Technology Engineering and Mathematics), and their teachers, with regional
    university research labs and provides them with the opportunity to work with
    researchers and graduate students on team-based, year-long network science
    research projects, culminating in a formal presentation at a network science
    conference. This short paper reports the content and materials that we have
    developed to date, including lesson plans and tools for introducing high school
    students and teachers to network science; empirical evaluation data on the
    effect of participation on students' motivation and interest in pursuing STEM
    careers; the application of professional development materials for teachers
    that are intended to encourage them to use network science concepts in their
    lesson plans and curriculum; promoting district-level interest and engagement;
    best practices gained from our experiences; and the future goals for this
    project and its subsequent outgrowth.

    DOI

    Scopus

    12
    Citation
    (Scopus)
  • Mental disorder recovery correlated with centralities and interactions on an online social network.

    Xinpei Ma, Hiroki Sayama

    PeerJ   3   e1163  2015  [Refereed]  [International journal]

     View Summary

    Recent research has established both a theoretical basis and strong empirical evidence that effective social behavior plays a beneficial role in the maintenance of physical and psychological well-being of people. To test whether social behavior and well-being are also associated in online communities, we studied the correlations between the recovery of patients with mental disorders and their behaviors in online social media. As the source of the data related to the social behavior and progress of mental recovery, we used PatientsLikeMe (PLM), the world's first open-participation research platform for the development of patient-centered health outcome measures. We first constructed an online social network structure based on patient-to-patient ties among 200 patients obtained from PLM. We then characterized patients' online social activities by measuring the numbers of "posts and views" and "helpful marks" each patient obtained. The patients' recovery data were obtained from their self-reported status information that was also available on PLM. We found that some node properties (in-degree, eigenvector centrality and PageRank) and the two online social activity measures were significantly correlated with patients' recovery. Furthermore, we re-collected the patients' recovery data two months after the first data collection. We found significant correlations between the patients' social behaviors and the second recovery data, which were collected two months apart. Our results indicated that social interactions in online communities such as PLM were significantly associated with the current and future recoveries of patients with mental disorders.

    DOI PubMed

    Scopus

    9
    Citation
    (Scopus)
  • Effects of Social Network Size and Topology on Evolutionary Decision Making.

    Hiroki Sayama, Shelley D. Dionne, Francis J. Yammarino

    Proceedings of the Thirteenth European Conference Artificial Life, ECAL 2015, York, UK, July 20-24, 2015   13   603 - 603  2015  [Refereed]

    DOI

    Scopus

  • Comparing two human disease networks: Gene-based and symptom-based perspectives

    Yousuf Shah, Ibraheem Rehman, Cheryl Limer, Zach Eaton, Carol Reynolds, Alan Troidl, Kristie McHugh, Hiroki Sayama, Genki Ichinose

    2015 5th IEEE Integrated STEM Education Conference (ISEC)     153 - 155  2015  [Refereed]

    DOI

    Scopus

  • Classification Analysis of Chronological Age Using Brief Resting Electroencephalographic (EEG) Recordings.

    Miaolin Fan, Vladimir Miskovic, Chun-An Chou, Sina Khanmohammadi, Hiroki Sayama, Brandon E. Gibb

    BRAIN INFORMATICS AND HEALTH (BIH 2015)   9250   96 - 104  2015  [Refereed]

     View Summary

    The present study aims to build a classification model that discriminates between chronological ages of subjects based on resting-state electroencephalography (EEG) data collected from a community sample of 269 children aged 7 to 11. Specifically, spectral power densities in four classical frequency bands: Delta (0.5-3 Hz), Theta (4-7 Hz), Alpha (8-12 Hz) and Beta (14-25 Hz) were extracted for each electrode as features, and fed to three classification algorithms including logistic regression (LR), support vector machine (SVM), and least absolute shrinkage and selection operator (Lasso). In addition, principal component analysis (PCA) was used to reduce the dimensions of the feature space. The results demonstrated that SVM and Lasso evidenced better performance (maximal accuracy = 80.68 +/- 2.01% by SVM and 77.82 +/- 2.11% by Lasso) when applied to original feature space, but LR yielded the best performance with PCA (80.72 +/- 1.73%). The accuracy of binary classification exhibited a decreasing trend with diminishing chronological gaps between the groups.

    DOI

    Scopus

  • Behavioral Diversities of Morphogenetic Collective Systems.

    Hiroki Sayama

    Proceedings of the Thirteenth European Conference Artificial Life, ECAL 2015, York, UK, July 20-24, 2015     41 - 41  2015  [Refereed]

    DOI

    Scopus

    3
    Citation
    (Scopus)
  • Theoretical investigation on the Schelling's critical neighborhood demand

    Jae Kyun Shin, Hiroki Sayama

    COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION   19 ( 5 ) 1417 - 1423  2014.02  [Refereed]

     View Summary

    We derived the critical neighborhood demand in the Schelling's segregation
    model by studying the conditions for which a chain reaction of migrations of
    unsatisfied agents occurs. The essence of Schelling dynamics was approximated
    in two simplified models: (1) a random walk model for the initial stage of the
    migrations to illustrate the power-law behavior of chain reaction lengths under
    critical conditions, and (2) a two-room model for the whole process to
    represent a non-spatial version of segregation dynamics in the Schelling model.
    Our theoretical results showed good agreements with numerical results obtained
    from agent-based simulations.

    DOI

    Scopus

    3
    Citation
    (Scopus)
  • A state equation for the Schelling's segregation model

    Jae Kyun Shin, Hiroki Sayama, Seung Ryul Choi

    COMPLEX & INTELLIGENT SYSTEMS   2 ( 1 ) 35 - 43  2014.02  [Refereed]

     View Summary

    An aspatial version for the famous Schelling's segregation model has recently
    been proposed, which, called two-room model, is still in an agent-based format
    like the original Schelling model. In the present study, we propose a new,
    state equation version of the Schelling model. The new equation is based on the
    two-room model and is derived in terms of a set of discrete maps. Fixed point
    solutions for the new equation are found analytically and confirmed
    numerically. Especially, we show that the extremely simple state equations can
    reasonably reveal the essence of the Schelling dynamics: integration,
    segregation and tipping. In addition to the fixed point solutions, periodic
    solutions are identified and conditions of the limit cycles are derived
    analytically.

    DOI

  • Theoretical investigation on the Schelling’s critical neighborhood demand

    Shin, Jae Kyun, Sayama, Hiroki

    Communications in Nonlinear Science and Numerical Simulation   19 ( 5 ) 1417 - 1423  2014  [Refereed]

     View Summary

    We derived the critical neighborhood demand in the Schelling's segregation model by studying the conditions for which a chain reaction of migrations of unsatisfied agents occurs. The essence of Schelling dynamics was approximated in two simplified models: (1) a random walk model for the initial stage of the migrations to illustrate the power-law behavior of chain reaction lengths under critical conditions, and (2) a two-room model for the whole process to represent a non-spatial version of segregation dynamics in the Schelling model. Our theoretical results showed good agreements with numerical results obtained from agent-based simulations. (C) 2013 Elsevier B. V. All rights reserved.

    DOI

    Scopus

    3
    Citation
    (Scopus)
  • Social Diffusion and Global Drift on Networks.

    Hiroki Sayama, Roberta Sinatra

    CoRR   abs/1410.3506 ( 3 ) 032809  2014  [Refereed]

     View Summary

    We study a mathematical model of social diffusion on a symmetric weighted
    network where individual nodes' states gradually assimilate to local social
    norms made by their neighbors' average states. Unlike physical diffusion, this
    process is not state conservational and thus the global state of the network
    (i.e., sum of node states) will drift. The asymptotic average node state will
    be the average of initial node states weighted by their strengths. Here we show
    that, while the global state is not conserved in this process, the inner
    product of strength and state vectors is conserved instead, and perfect
    positive correlation between node states and local averages of their
    self/neighbor strength ratios always results in upward (or at least neutral)
    global drift. We also show that the strength assortativity negatively affects
    the speed of homogenization. Based on these findings, we propose an adaptive
    link weight adjustment method to achieve the highest upward global drift by
    increasing the strength-state correlation. The effectiveness of the method was
    confirmed through numerical simulations and implications for real-world social
    applications are discussed.

    DOI

    Scopus

    3
    Citation
    (Scopus)
  • Hierarchical Heterogeneous Particle Swarm Optimization

    Ma Xinpei, Sayama Hiroki

    ALIFE 14: The Fourteenth Conference on the Synthesis and Simulation of Living Systems   14   3  2014  [Refereed]

  • Artificial Life 14: Proceedings of the Fourteenth International Conference on the Synthesis and Simulation of Living Systems (ALIFE 14)

    Hiroki Sayama John Rieffel Sebastian, Risi Ren{\'e, Doursat, Hod, Lipson eds

       2014  [Refereed]

  • Invasion of cooperation in scale-free networks: Accumulated vs. average payoffs

    Ichinose Genki, Sayama Hiroki

    ALIFE 14: The Fourteenth Conference on the Synthesis and Simulation of Living Systems   14   398  2014  [Refereed]

  • Social diffusion and global drift in adaptive social networks.

    Hiroki Sayama

    CoRR   abs/1406.7585   Paper  2014  [Refereed]

     View Summary

    Social contagion has been studied in various contexts. Many instances of
    social contagion can be modeled as an infection process where a specific state
    (adoption of product, fad, knowledge, behavior, etc.) spreads from individual
    to individual through links between them. In the meantime, other forms of
    social contagion may better be understood as a diffusion process where the
    state of an individual tends to assimilate with the social norm (i.e., local
    average state) within his/her neighborhood.
    Unlike infection scenarios where influence is nonlinear, unidirectional,
    fast, and potentially disruptive, social diffusion is linear, bidirectional,
    gradual, and converging. The distance between an individual's state and his/her
    neighbors' average state always decreases, and thus a homogeneous global state
    is guaranteed to be the network's stable equilibrium state in the long run.
    This does not sound as intriguing or exciting as infection dynamics, which
    might be why there are very few studies on mathematical models of social
    diffusion processes.
    Here, this study attempts to shed new light on an unrecognized characteristic
    of social diffusion, i.e., non-trivial drift it can cause to the network's
    global average state. Although somewhat counterintuitive, such global drift is
    indeed possible because, unlike physical diffusion processes, social diffusion
    processes are not conservational. In what follows, a mathematical model of
    social diffusion will be presented to explain the mechanism of this phenomenon,
    and some possible collective actions for influencing the direction of global
    drift will be proposed. The relevance of social diffusion to individual and
    collective improvement will be discussed briefly, with an emphasis on
    educational applications.

  • Four Classes of Morphogenetic Collective Systems.

    Hiroki Sayama

    CoRR   abs/1405.6296 ( http://arxiv.org/abs/1405.6296 ) 320  2014  [Refereed]

     View Summary

    We studied the roles of morphogenetic principles---heterogeneity of
    components, dynamic differentiation/re-differentiation of components, and local
    information sharing among components---in the self-organization of
    morphogenetic collective systems. By incrementally introducing these principles
    to collectives, we defined four distinct classes of morphogenetic collective
    systems. Monte Carlo simulations were conducted using an extended version of
    the Swarm Chemistry model that was equipped with dynamic
    differentiation/re-differentiation and local information sharing capabilities.
    Self-organization of swarms was characterized by several kinetic and
    topological measurements, the latter of which were facilitated by a newly
    developed network-based method. Results of simulations revealed that, while
    heterogeneity of components had a strong impact on the structure and behavior
    of the swarms, dynamic differentiation/re-differentiation of components and
    local information sharing helped the swarms maintain spatially adjacent,
    coherent organization.

  • Evolution of Fairness in the Not Quite Ultimatum Game

    Ichinose, Genki, Sayama, Hiroki

    Scientific Reports   4   5104 - 5104  2014  [Refereed]  [International journal]

     View Summary

    The Ultimatum Game (UG) is an economic game where two players (proposer and responder) decide how to split a certain amount of money. While traditional economic theories based on rational decision making predict that the proposer should make a minimal offer and the responder should accept it, human subjects tend to behave more fairly in UG. Previous studies suggested that extra information such as reputation, empathy, or spatial structure is needed for fairness to evolve in UG. Here we show that fairness can evolve without additional information if players make decisions probabilistically and may continue interactions when the offer is rejected, which we call the Not Quite Ultimatum Game (NQUG). Evolutionary simulations of NQUG showed that the probabilistic decision making contributes to the increase of proposers' offer amounts to avoid rejection, while the repetition of the game works to responders' advantage because they can wait until a good offer comes. These simple extensions greatly promote evolution of fairness in both proposers' offers and responders' acceptance thresholds.

    DOI PubMed

    Scopus

    24
    Citation
    (Scopus)
  • NetSci High: Bringing Network Science Research to High Schools.

    Catherine Cramer, Lori Sheetz, Hiroki Sayama, Paul Trunfio, Harry Eugene Stanley, Stephen M. Uzzo

    CoRR   abs/1412.3125  2014

  • Studying Collective Human Decision Making and Creativity with Evolutionary Computation.

    Hiroki Sayama, Shelley D. Dionne

    CoRR   abs/1406.6291  2014

  • Spread of Academic Success in a High School Social Network

    Blansky, Deanna, Kavanaugh, Christina, Boothroyd, Cara, Benson, Brianna, Gallagher, Julie, Endress, John, Sayama, Hiroki

    PLOS ONE   8 ( 2 ) e55944  2013  [Refereed]

     View Summary

    Application of social network analysis to education has revealed how social network positions of K-12 students correlate with their behavior and academic achievements. However, no study has been conducted on how their social network influences their academic progress over time. Here we investigated correlations between high school students' academic progress over one year and the social environment that surrounds them in their friendship network. We found that students whose friends' average GPA (Grade Point Average) was greater (or less) than their own had a higher tendency toward increasing (or decreasing) their academic ranking over time, indicating social contagion of academic success taking place in their social network.

    DOI

    Scopus

    33
    Citation
    (Scopus)
  • Proceedings of the Fourth IEEE Symposium on Artificial Life (IEEE ALIFE 2013)

    Nehaniv Chrystopher, Bossomaier Terry, Sayama Hiroki

       2013  [Refereed]

  • Post-merger cultural integration from a social network perspective: a computational modeling approach

    Yamanoi, Junichi, Sayama, Hiroki

    Computational and Mathematical Organization Theory   19 ( 4 ) 516 - 537  2013  [Refereed]

     View Summary

    Although cultural integration, or sharing a common corporate culture, is crucial for the success of mergers, previous studies have been limited to firm-level analyses. From a social network perspective, this study explores how cultural integration emerges from the patterns of social interactions among individuals. Using an agent-based model, we investigate the impact of network structures within and between two merging firms on post-merger cultural integration and organizational dysfunctions-individual turnover, interpersonal conflict and organizational communication ineffectiveness-that arise from insufficient cultural integration. The simulation results demonstrate that the highest level of cultural integration is achieved when social ties are more centralized within each merging firm and the social ties between the merging firms are less concentrated on central individuals. Additionally, the results show that within-firm and between-firm network structures significantly affect individual turnover, interpersonal conflict and organizational communication ineffectiveness, and that these three outcome measurements do not vary in tandem.

    DOI

    Scopus

    13
    Citation
    (Scopus)
  • Modeling Lyme disease risk using a biobehavioral and ecological approach.

    Kommareddy D, Schmidt J, Darcy JM, Garruto RM, Sayama H

    AMERICAN JOURNAL OF HUMAN BIOLOGY   25 ( 2 ) 263  2013  [Refereed]

  • A Review of Morphogenetic Engineering

    Doursat, Ren{\'e}, Sayama, Hiroki, Michel, Olivier

    Natural Computing   12 ( 4 ) 517 - 535  2013  [Refereed]

     View Summary

    Generally, phenomena of spontaneous pattern formation are random and repetitive, whereas elaborate devices are the deterministic product of human design. Yet, biological organisms and collective insect constructions are exceptional examples of complex systems (CS) that are both architectured and self-organized. Can we understand their precise self-formation capabilities and integrate them with technological planning? Can physical systems be endowed with information, or informational systems be embedded in physics, to create autonomous morphologies and functions? To answer these questions, we have launched in 2009, and developed through a series of workshops and a collective book, a new field of research called morphogenetic engineering. It is the first initiative of its kind to rally and promote models and implementations of complex self-architecturing systems. Particular emphasis is set on the programmability and computational abilities of self-organization, properties that are often underappreciated in CS science-while, conversely, the benefits of self-organization are often underappreciated in engineering methodologies. [This paper is an extended version of Doursat, Sayama and Michel (2012b) (Chapter 1, in Doursat R et al. (eds.) Morphogenetic engineering: toward programmable complex systems. Understanding complex systems. Springer, 2012a).]

    DOI

    Scopus

    85
    Citation
    (Scopus)
  • A meme propagation model based on kinetic interaction of particles

    Kobayashi Kengo, Suzuki Reiji, Arita Takaya, Sayama Hiroki

    Proceedings of the 25th Distributed Autonomous Systems Symposium, Sendai, Japan    2013  [Refereed]

  • Adaptive long-range migration promotes cooperation under tempting conditions

    Ichinose, Genki, Saito, Masaya, Sayama, Hiroki, Wilson, David Sloan

    Scientific reports   3   2509 - 2509  2013  [Refereed]  [International journal]

     View Summary

    Migration is a fundamental trait in humans and animals. Recent studies investigated the effect of migration on the evolution of cooperation, showing that contingent migration favors cooperation in spatial structures. In those studies, only local migration to immediate neighbors was considered, while long-range migration has not been considered yet, partly because the long-range migration has been generally regarded as harmful for cooperation as it would bring the population to a well-mixed state that favors defection. Here, we studied the effects of adaptive long-range migration on the evolution of cooperation through agent-based simulations of a spatial Prisoner's Dilemma game where individuals can jump to a farther site if they are surrounded by more defectors. Our results show that adaptive long-range migration strongly promotes cooperation, especially under conditions where the temptation to defect is considerably high. These findings demonstrate the significance of adaptive long-range migration for the evolution of cooperation.

    DOI PubMed

    Scopus

    51
    Citation
    (Scopus)
  • Emergence, transmission, and risk of Lyme disease and other tick-borne infections: a community based natural experimental model

    Darcy JM, Spathis R, Schmidt J, Keppler H, Hempstead S, Cruz T, Kommareddy D, Thomas J, Riddle M, Sayama H, o

    AMERICAN JOURNAL OF HUMAN BIOLOGY   25 ( 2 ) 255  2013  [Refereed]

  • Using evolutionary computation as models/tools for human decision making and creativity research.

    Hiroki Sayama, Shelley D. Dionne

    2013 IEEE SYMPOSIUM ON ARTIFICIAL LIFE (ALIFE)     35 - 42  2013  [Refereed]

     View Summary

    This paper presents a review of our recently completed interdisciplinary research project "Evolutionary Perspective on Collective Decision Making" that was conducted through close collaboration between computational, organizational and social scientists at Binghamton University. In this project, we utilized Evolutionary Computation in several non-traditional ways-(1) as a theoretical framework for reinterpreting the dynamics of collective human decision making processes, (2) as a computational simulation model of idea generation and selection, and (3) as a research tool for collecting high-resolution experimental data of actual collaborative design and decision making from human subjects.

    DOI

    Scopus

    1
    Citation
    (Scopus)
  • Spread of academic success in a high school social network.

    Deanna Blansky, Christina Kavanaugh, Cara Boothroyd, Brianna Benson, Julie Gallagher, John Endress, Hiroki Sayama

    PloS one   8 ( 2 ) e55944  2013  [Refereed]  [International journal]

     View Summary

    Application of social network analysis to education has revealed how social network positions of K-12 students correlate with their behavior and academic achievements. However, no study has been conducted on how their social network influences their academic progress over time. Here we investigated correlations between high school students' academic progress over one year and the social environment that surrounds them in their friendship network. We found that students whose friends' average GPA (Grade Point Average) was greater (or less) than their own had a higher tendency toward increasing (or decreasing) their academic ranking over time, indicating social contagion of academic success taking place in their social network.

    DOI PubMed

    Scopus

    33
    Citation
    (Scopus)
  • PyCX: a Python-based simulation code repository for complex systems education

    Sayama, Hiroki

    Complex Adaptive Systems Modeling   1 ( 1 ) 2 - 2  2013  [Refereed]

    DOI

    Scopus

    15
    Citation
    (Scopus)
  • Post-merger cultural integration from a social network perspective: a computational modeling approach.

    Junichi Yamanoi, Hiroki Sayama

    Comput. Math. Organ. Theory   19 ( 4 ) 516 - 537  2013  [Refereed]

     View Summary

    Although cultural integration, or sharing a common corporate culture, is crucial for the success of mergers, previous studies have been limited to firm-level analyses. From a social network perspective, this study explores how cultural integration emerges from the patterns of social interactions among individuals. Using an agent-based model, we investigate the impact of network structures within and between two merging firms on post-merger cultural integration and organizational dysfunctions-individual turnover, interpersonal conflict and organizational communication ineffectiveness-that arise from insufficient cultural integration. The simulation results demonstrate that the highest level of cultural integration is achieved when social ties are more centralized within each merging firm and the social ties between the merging firms are less concentrated on central individuals. Additionally, the results show that within-firm and between-firm network structures significantly affect individual turnover, interpersonal conflict and organizational communication ineffectiveness, and that these three outcome measurements do not vary in tandem.

    DOI

    Scopus

    13
    Citation
    (Scopus)
  • Modeling complex systems with adaptive networks

    Sayama, Hiroki, Pestov, Irene, Schmidt, Jeffrey, Bush, Benjamin James, Wong, Chun, Yamanoi, Junichi, Gross, Thilo

    Computers & Mathematics with Applications   65 ( 10 ) 1645 - 1664  2013  [Refereed]

     View Summary

    Adaptive networks are a novel class of dynamical networks whose topologies
    and states coevolve. Many real-world complex systems can be modeled as adaptive
    networks, including social networks, transportation networks, neural networks
    and biological networks. In this paper, we introduce fundamental concepts and
    unique properties of adaptive networks through a brief, non-comprehensive
    review of recent literature on mathematical/computational modeling and analysis
    of such networks. We also report our recent work on several applications of
    computational adaptive network modeling and analysis to real-world problems,
    including temporal development of search and rescue operational networks,
    automated rule discovery from empirical network evolution data, and cultural
    integration in corporate merger.

    DOI

    Scopus

    118
    Citation
    (Scopus)
  • Impact of Personal Fabrication Technology on Social Structure and Wealth Distribution: An Agent-Based Simulation Study.

    Amber Ferger, Wai Fai Lau, Philipp Ross, Wyman Zhao, Hiroki Sayama, Steen Rasmussen

    Proceedings of the Twelfth European Conference on the Synthesis and Simulation of Living Systems: Advances in Artificial Life, ECAL 2013, Sicily, Italy, September 2-6, 2013   12   521 - 522  2013  [Refereed]

    DOI

    Scopus

    1
    Citation
    (Scopus)
  • Guiding designs of self-organizing swarms: Interactive and automated approaches

    Sayama, Hiroki

    arXiv preprint   abs/1308.3400   http - arxiv  2013  [Refereed]

     View Summary

    Self-organization of heterogeneous particle swarms is rich in its dynamics
    but hard to design in a traditional top-down manner, especially when many types
    of kinetically distinct particles are involved. In this chapter, we discuss how
    we have been addressing this problem by (1) utilizing and enhancing interactive
    evolutionary design methods and (2) realizing spontaneous evolution of self
    organizing swarms within an artificial ecosystem.

  • Evolutionary perspectives on collective decision making: Studying the implications of diversity and social network structure with agent-based simulations

    Sayama, Hiroki, Dionne, Shelley D., Yammarino, Francis J.

    arXiv.org   abs/1311.3674 ( http://arxiv.org/abs/1311.3674 ) 40 - pages  2013  [Refereed]

  • Designing and evaluating algorithms for automated discovery of adaptive network models based on generative network automata.

    Jeffrey Schmidt, Hiroki Sayama

    IEEE Symposium on Artificial Life, ALife 2013, Singapore, April 16-19, 2013     27 - 34  2013  [Refereed]

     View Summary

    Generative Network Automata (GNA) is a powerful tool for the study of adaptive networks. It has the ability to represent a wide range of dynamics by leveraging its inherent generality. The ability to automatically discover underlying dynamics of adaptive network input has been theoretically proposed using GNA. This work tries to answer the question as to whether it is possible to create a practical implementation of GNA for the automatic discovery of dynamical rules that capture the state transition and topological transformation of complex adaptive networks. The results show that our algorithms and software (called PyGNA) correctly identifies the dynamics of a set of simple adaptive networks. Capturing the dynamics of more complex adaptive networks remains a challenge that will require further algorithm improvement.

    DOI

  • Adaptive long-range migration promotes cooperation under tempting conditions.

    Genki Ichinose, Masaya Saito, Hiroki Sayama, David Sloan Wilson

    SCIENTIFIC REPORTS   3   1220 - 1221  2013  [Refereed]

     View Summary

    Migration is a fundamental trait in humans and animals. Recent studies investigated the effect of migration on the evolution of cooperation, showing that contingent migration favors cooperation in spatial structures. In those studies, only local migration to immediate neighbors was considered, while long-range migration has not been considered yet, partly because the long-range migration has been generally regarded as harmful for cooperation as it would bring the population to a well-mixed state that favors defection. Here, we studied the effects of adaptive long-range migration on the evolution of cooperation through agent-based simulations of a spatial Prisoner's Dilemma game where individuals can jump to a farther site if they are surrounded by more defectors. Our results show that adaptive long-range migration strongly promotes cooperation, especially under conditions where the temptation to defect is considerably high. These findings demonstrate the significance of adaptive long-range migration for the evolution of cooperation.

    DOI PubMed

    Scopus

  • A review of morphogenetic engineering.

    René Doursat, Hiroki Sayama, Olivier Michel

    Nat. Comput.   12 ( 4 ) 517 - 535  2013  [Refereed]

     View Summary

    Generally, phenomena of spontaneous pattern formation are random and repetitive, whereas elaborate devices are the deterministic product of human design. Yet, biological organisms and collective insect constructions are exceptional examples of complex systems (CS) that are both architectured and self-organized. Can we understand their precise self-formation capabilities and integrate them with technological planning? Can physical systems be endowed with information, or informational systems be embedded in physics, to create autonomous morphologies and functions? To answer these questions, we have launched in 2009, and developed through a series of workshops and a collective book, a new field of research called morphogenetic engineering. It is the first initiative of its kind to rally and promote models and implementations of complex self-architecturing systems. Particular emphasis is set on the programmability and computational abilities of self-organization, properties that are often underappreciated in CS science-while, conversely, the benefits of self-organization are often underappreciated in engineering methodologies. [This paper is an extended version of Doursat, Sayama and Michel (2012b) (Chapter 1, in Doursat R et al. (eds.) Morphogenetic engineering: toward programmable complex systems. Understanding complex systems. Springer, 2012a).]

    DOI

    Scopus

    85
    Citation
    (Scopus)
  • A deterministic agent-particle model for cellular diffusion, aggregation and self-organization.

    Jean Marie Dembele, Hiroki Sayama

    2013 IEEE SYMPOSIUM ON ARTIFICIAL LIFE (ALIFE)     21 - 26  2013  [Refereed]

     View Summary

    This paper presents an agent-based model of cellular proliferation, taxis and spatial diffusion. Our model describes the behavior of individual cells, rather than the aggregate behavior of cell distributions, derived from a set of partial differential equations. The physical motions of cells - taxis toward higher concentration of nutrients and diffusion in space - arc handled in a deterministic way, which is a unique, distinctive feature of our model compared to other stochastic simulation models. The model is tested with some simple assumptions to show interesting self-organizing behaviors.

    DOI

    Scopus

    4
    Citation
    (Scopus)
  • Modeling complex systems with adaptive networks

    Hiroki Sayama, Irene Pestov, Jeffrey Schmidt, Benjamin James Bush, Chun Wong, Junichi Yamanoi, Thilo Gross

    CoRR   abs/1301.2561  2013

  • Retrospective Relatedness Reconstruction: Applications to Adaptive Social Networks and Social Sentiment

    Shelley D. Dionne, Jin Akaishi, Xiujian Chen, Alka Gupta, Hiroki Sayama, Francis J. Yammarino, Andra Serban, Chanyu Hao, Hadassah J. Head, Benjamin James Bush

    ORGANIZATIONAL RESEARCH METHODS   15 ( 4 ) 663 - 692  2012.10  [Refereed]

     View Summary

    Examination of temporally changing adaptive social networks has been difficult given the need for extensive and usually real-time data collection. Building from interdisciplinary advances, the authors propose a web search engine-based method (called retrospective relatedness reconstruction or 3R) for collecting approximated historical data of temporally changing adaptive social networks. As quantifying relatedness among people in social networks leads to difficulty in assigning proper weights to relationship ties, 3R offers a means for assessing relatedness between people over time. Additionally, 3R can be applied beyond people relatedness to include word associations. To illustrate these two novel contributions, the authors reconstructed the temporal evolution of a social network from 2005 to 2009 of 92 individuals (key leaders) related to the U.S. financial crisis and also examined the temporal evolution of social sentiment (i.e., fear, shame, blame, confidence) related to the same 92 individuals. We found several illustrative cases where temporal changes in centrality and/or sentiment captured actual events related to these individuals during this time period.

    DOI

    Scopus

    10
    Citation
    (Scopus)
  • Retrospective Relatedness Reconstruction: Applications to Adaptive Social Networks and Social Sentiment

    Dionne, Shelley D, Akaishi, Jin, Chen, Xiujian, Gupta, Alka, Sayama, Hiroki, Yammarino, Francis J, Serban, Andra, Hao, Chanyu, Head, Hadassah J, Bush, Benjamin James

    Organizational Research Methods   15 ( 4 ) 663 - 692  2012  [Refereed]

     View Summary

    Examination of temporally changing adaptive social networks has been difficult given the need for extensive and usually real-time data collection. Building from interdisciplinary advances, the authors propose a web search engine-based method (called retrospective relatedness reconstruction or 3R) for collecting approximated historical data of temporally changing adaptive social networks. As quantifying relatedness among people in social networks leads to difficulty in assigning proper weights to relationship ties, 3R offers a means for assessing relatedness between people over time. Additionally, 3R can be applied beyond people relatedness to include word associations. To illustrate these two novel contributions, the authors reconstructed the temporal evolution of a social network from 2005 to 2009 of 92 individuals (key leaders) related to the U.S. financial crisis and also examined the temporal evolution of social sentiment (i.e., fear, shame, blame, confidence) related to the same 92 individuals. We found several illustrative cases where temporal changes in centrality and/or sentiment captured actual events related to these individuals during this time period.

    DOI

    Scopus

    10
    Citation
    (Scopus)
  • Morphogenetic Engineering: Toward Programmable Complex Systems

    Doursat, R, Sayama, H, Michel, O

    NECSI Studies on Complexity, Springer, forthcoming    2012  [Refereed]

    DOI

  • Modeling discrete distributed heterogeneous systems

    Pestov Irene, Sayama Hiroki, Wong Chun

    Proc. Int. Conf. on Modeling, Simulation and Visualization Methods (MSV 2012)    2012  [Refereed]

  • Modeling co-evolution of states and topologies of adaptive networks

    Sayama Hiroki

    Proceedings of EvoNet2012: ALIFE 13 Workshop on Evolving Networks, from Systems/Synthetic Biology to Computational Neuroscience     3  2012  [Refereed]

  • Evolutionary Swarm Chemistry in three-dimensions

    Sayama Hiroki

    Artificial Life 13: Proceedings of the Thirteenth International Conference on the Simulation and Synthesis of Living Systems     576  2012  [Refereed]

  • Characterizing Interdisciplinarity of Researchers and Research Topics Using Web Search Engines

    Sayama, Hiroki, Akaishi, Jin

    PloS one   7 ( 6 ) e38747  2012  [Refereed]

     View Summary

    Researchers' networks have been subject to active modeling and analysis. Earlier literature mostly focused on citation or co-authorship networks reconstructed from annotated scientific publication databases, which have several limitations. Recently, general-purpose web search engines have also been utilized to collect information about social networks. Here we reconstructed, using web search engines, a network representing the relatedness of researchers to their peers as well as to various research topics. Relatedness between researchers and research topics was characterized by visibility boost-increase of a researcher's visibility by focusing on a particular topic. It was observed that researchers who had high visibility boosts by the same research topic tended to be close to each other in their network. We calculated correlations between visibility boosts by research topics and researchers' interdisciplinarity at the individual level (diversity of topics related to the researcher) and at the social level (his/her centrality in the researchers' network). We found that visibility boosts by certain research topics were positively correlated with researchers' individual-level interdisciplinarity despite their negative correlations with the general popularity of researchers. It was also found that visibility boosts by network-related topics had positive correlations with researchers' social-level interdisciplinarity. Research topics' correlations with researchers' individual- and social-level interdisciplinarities were found to be nearly independent from each other. These findings suggest that the notion of "interdisciplinarity" of a researcher should be understood as a multi-dimensional concept that should be evaluated using multiple assessment means.

    DOI

    Scopus

    14
    Citation
    (Scopus)
  • An Algorithm for Automatically Discovering Dynamical Rules of Adaptive Network Evolution from Empirical Data

    Sayama, Hiroki

    Bio-Inspired Models of Network, Information, and Computing Systems     497 - 504  2012  [Refereed]

    DOI

    Scopus

    2
    Citation
    (Scopus)
  • Swarm-Based Morphogenetic Artificial Life

    Sayama, Hiroki

    Morphogenetic Engineering     191 - 208  2012  [Refereed]

    DOI

  • Morphologies of self-organizing swarms in 3D swarm chemistry.

    Hiroki Sayama

    PROCEEDINGS OF THE FOURTEENTH INTERNATIONAL CONFERENCE ON GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE     577 - 584  2012  [Refereed]

     View Summary

    A three-dimensional version of the Swarm Chemistry model is presented. Self-organization and morphogenesis of heterogeneous swarms in the 3D model were compared to those in the original 2D version. It was observed that the resulting patterns generally had remarkable robustness against dimensionality change, while some swarms were susceptible to the change. Further experiments showed that it was often sufficient to make minimal parameter adjustments in order to recover the original topological and dynamical properties of those susceptible swarms in 3D, although the dependence on parameters varied case by case with no generic parameter mapping between 2D and 3D.

    DOI

    Scopus

    14
    Citation
    (Scopus)
  • Morphogenetic Engineering: Reconciling self-organization and architecture

    Doursat, Ren{\'e}, Sayama, Hiroki, Michel, Olivier

    Morphogenetic Engineering     1 - 24  2012  [Refereed]

    DOI

  • Evolving data sets to highlight the performance differences between machine learning classifiers.

    Thomas Raway, J. David Schaffer, Kenneth J. Kurtz, Hiroki Sayama

    PROCEEDINGS OF THE FOURTEENTH INTERNATIONAL CONFERENCE ON GENETIC AND EVOLUTIONARY COMPUTATION COMPANION (GECCO'12)     657 - 658  2012  [Refereed]

     View Summary

    We present a preliminary study to evolve data sets that maximize performance differences between multiple machine learning classifiers. The aim is to provide useful information towards the decision of which machine learning classifier to use given a particular data set. While literature already exists on comparing multiple classifiers across multiple pre-existing data sets, our approach is novel and unique in that we evolved completely new data sets designed to highlight the performance differences between supervised learning classifiers. By investigating these evolved data sets, we hope to add to the knowledge base concerning which classifiers are appropriate for specific real world classification tasks.

    DOI

    Scopus

    2
    Citation
    (Scopus)
  • Characterizing interdisciplinarity of researchers and research topics using web search engines.

    Hiroki Sayama, Jin Akaishi

    PloS one   7 ( 6 ) e38747  2012  [Refereed]  [International journal]

     View Summary

    Researchers' networks have been subject to active modeling and analysis. Earlier literature mostly focused on citation or co-authorship networks reconstructed from annotated scientific publication databases, which have several limitations. Recently, general-purpose web search engines have also been utilized to collect information about social networks. Here we reconstructed, using web search engines, a network representing the relatedness of researchers to their peers as well as to various research topics. Relatedness between researchers and research topics was characterized by visibility boost-increase of a researcher's visibility by focusing on a particular topic. It was observed that researchers who had high visibility boosts by the same research topic tended to be close to each other in their network. We calculated correlations between visibility boosts by research topics and researchers' interdisciplinarity at the individual level (diversity of topics related to the researcher) and at the social level (his/her centrality in the researchers' network). We found that visibility boosts by certain research topics were positively correlated with researchers' individual-level interdisciplinarity despite their negative correlations with the general popularity of researchers. It was also found that visibility boosts by network-related topics had positive correlations with researchers' social-level interdisciplinarity. Research topics' correlations with researchers' individual- and social-level interdisciplinarities were found to be nearly independent from each other. These findings suggest that the notion of "interdisciplinarity" of a researcher should be understood as a multi-dimensional concept that should be evaluated using multiple assessment means.

    DOI PubMed

    Scopus

    14
    Citation
    (Scopus)
  • The effects of mental model formation on group decision making: An agent-based simulation

    Sayama, Hiroki, Farrell, Dene L, Dionne, Shelley D

    Complexity   16 ( 3 ) 49 - 57  2011  [Refereed]

     View Summary

    We investigated dynamics of group decision making on complex problems when agents can form mental models of others from discussion history. Results indicated that as the agents' memory capacity increases, the group reaches superficial consensus more easily. Surprisingly, however, the shared mental model of the problem develops only within a limited area of the problem space, because incorporating knowledge from others into one's own knowledge quickly creates local agreement on where relevant solutions are, leaving other potentially useful solutions beyond the scope of discussion. The mechanisms stifling group-level exploration and their implications for decision making research are discussed. (C) 2010 Wiley Periodicals, Inc. Complexity 16: 49-57, 2011

    DOI

    Scopus

    28
    Citation
    (Scopus)
  • Proceedings of the 2011 IEEE Symposium on Artificial Life (IEEE ALIFE 2011)

    Nehaniv Chrystopher L, Bossomaier Terry, Sayama Hiroki

       2011  [Refereed]

  • POSITIVE STEREOTYPING AND MULTICULTURAL AWARENESS: AN ONLINE EXPERIMENT

    Sayama, Mari, Sayama, Hiroki

    Current Research in Social Psychology (CRISP)    2011  [Refereed]

  • Modeling Geographical Diffusion of Broadband Internet Use from Household Survey Data

    Wong, Chun, Sayama, Hiroki, Agarwal, Manoj, Chiu, Kenneth, Heard, Kevin

       2011  [Refereed]

  • Hyperinteractive evolutionary computation

    Bush, Benjamin James, Sayama, Hiroki

    Evolutionary Computation, IEEE Transactions on   15 ( 99 ) 1 - 10  2011  [Refereed]

     View Summary

    We propose hyperinteractive evolutionary computation (HIEC), a class of IEC in which the user actively chooses when and how each evolutionary operator is applied. To evaluate the benefits of HIEC, we conducted three human-subject experiments. The first two experiments showed that HIEC is associated with a more positive user experience and produced higher quality designs. The third experiment demonstrates the potential of HIEC as a research tool with which one can record the evolutionary actions taken by human users. Implications, limitations, and future directions of research are discussed.

    DOI

    Scopus

    32
    Citation
    (Scopus)
  • Behavior and Centrality in Idea Exchanging Adaptive Social Networks

    Bush, Benjamin James, Schmidt, Jeffery, Sayama, Hiroki

       2011  [Refereed]

  • A Python Implementation of Generative Network Automata

    Schmidt, Jeffrey, Bush, Benjamin James, Sayama, Hiroki

       2011  [Refereed]

  • A Comparative Study on the Social Networks of Fictional Characters

    Calderone, Jessica, Valentine, Emma, Trichka, Josie, Gallagher, Julie, Bush, Benjamin James, Akaishi, Jin, Sayama, Hiroki

       2011  [Refereed]

  • The Effects of Mental Model Formation on Group Decision Making: An Agent-Based Simulation

    Hiroki Sayama, Dene L. Farrell, Shelley D. Dionne

    COMPLEXITY   16 ( 3 ) 49 - 57  2011.01  [Refereed]

     View Summary

    We investigated dynamics of group decision making on complex problems when agents can form mental models of others from discussion history. Results indicated that as the agents' memory capacity increases, the group reaches superficial consensus more easily. Surprisingly, however, the shared mental model of the problem develops only within a limited area of the problem space, because incorporating knowledge from others into one's own knowledge quickly creates local agreement on where relevant solutions are, leaving other potentially useful solutions beyond the scope of discussion. The mechanisms stifling group-level exploration and their implications for decision making research are discussed. (C) 2010 Wiley Periodicals, Inc. Complexity 16: 49-57, 2011

    DOI

    Scopus

    28
    Citation
    (Scopus)
  • Seeking open-ended evolution in Swarm Chemistry.

    Hiroki Sayama

    2011 IEEE Symposium on Artificial Life, ALIFE 2011, Paris, France, April 13-15, 2011     186 - 193  2011  [Refereed]

    DOI

    Scopus

    25
    Citation
    (Scopus)
  • Quantifying evolutionary dynamics of swarm chemistry.

    Hiroki Sayama, Chun Wong

    Advances in Artificial Life: 20th Anniversary Edition - Back to the Origins of Alife, ECAL 2011, Paris, France, August 8-12, 2011     729 - 730  2011  [Refereed]

  • Hyperinteractive Evolutionary Computation.

    Benjamin James Bush, Hiroki Sayama

    IEEE Trans. Evol. Comput.   15 ( 3 ) 424 - 433  2011  [Refereed]

     View Summary

    We propose hyperinteractive evolutionary computation (HIEC), a class of IEC in which the user actively chooses when and how each evolutionary operator is applied. To evaluate the benefits of HIEC, we conducted three human-subject experiments. The first two experiments showed that HIEC is associated with a more positive user experience and produced higher quality designs. The third experiment demonstrates the potential of HIEC as a research tool with which one can record the evolutionary actions taken by human users. Implications, limitations, and future directions of research are discussed.

    DOI

    Scopus

    32
    Citation
    (Scopus)
  • Genetic Stigmergy

    Br, off, Joshua, Sayama, Hiroki

    Bio-Inspired Self-Organizing Robotic Systems     81 - 103  2011  [Refereed]

    DOI

    Scopus

  • An artificial life view of the collatz problem

    Sayama, Hiroki

    Artificial Life   17 ( 2 ) 137 - 140  2011  [Refereed]  [International journal]

     View Summary

    This letter presents a new, artificial-life-based view of the Collatz problem, a well-known mathematical problem about the behavior of a series of positive integers generated by a simple arithmetical rule. The Collatz conjecture asserts that this series always falls into a 4 → 2 → 1 cycle regardless of its initial values. No formal proof has been given yet. In this letter, the behavior of the series is considered an ecological process of artificial organisms (1s in bit strings). The Collatz conjecture is then reinterpreted as the competition between population growth and extinction. This new interpretation has made it possible to analytically calculate the growth and extinction speeds of bit strings. The results indicate that the extinction is always faster than the growth, providing an ecological explanation for the conjecture. Future research directions are also suggested.

    DOI PubMed

    Scopus

    6
    Citation
    (Scopus)
  • The role of leadership in shared mental model convergence and team performance improvement An agent-based computational model

    Shelley D. Dionne, Hiroki Sayama, Chanyu Hao, Benjamin James Bush

    LEADERSHIP QUARTERLY   21 ( 6 ) 1035 - 1049  2010.12  [Refereed]

     View Summary

    Research in shared mental models has Immeasurably aided our understanding of effective teamwork and taskwork However little research has focused on the role that leaders play if any in influencing developing and/or fostering shared mental models and thereby improving team performance We developed an agent-based computational model based on McComb s theory of three-phase mental model development where agents repeatedly share individual opinions (orientation phase) evaluate and respond to the opinions expressed by others (differentiation phase) and modify their understanding of the team based on the responses (integration phase) Leadership and team properties are represented in three experimental parameters social network structure heterogeneity of agents domains of expertise and level of their mutual interest Participative leadership is represented by a fully connected network while Leader-Member exchange (LMX) is represented by a fully connected network of in group members and several out-group members connected only to the leader Our simulation results show that in general participative leadership promotes mental model convergence better than LMX In the meantime the team performance improvement is achieved by participative leadership only when members have both heterogeneous domains of expertise and strong mutual interest In all other conditions participative leadership causes the worst degradation of team performance through team development processes while LMX is the best to minimize such team degradation Implications and suggestions for future research are provided (c) 2010 Elsevier Inc All rights reserved

    DOI

    Scopus

    110
    Citation
    (Scopus)
  • Robust Morphogenesis of Robotic Swarms

    Hiroki Sayama

    IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE   5 ( 3 ) 43 - 49  2010.08  [Refereed]

    DOI

    Scopus

    33
    Citation
    (Scopus)
  • The role of leadership in shared mental model convergence and team performance improvement: An agent-based computational model

    Dionne, Shelley D, Sayama, Hiroki, Hao, Chanyu, Bush, Benjamin James

    The Leadership Quarterly   21 ( 6 ) 1035 - 1049  2010  [Refereed]

     View Summary

    Research in shared mental models has Immeasurably aided our understanding of effective teamwork and taskwork However little research has focused on the role that leaders play if any in influencing developing and/or fostering shared mental models and thereby improving team performance We developed an agent-based computational model based on McComb s theory of three-phase mental model development where agents repeatedly share individual opinions (orientation phase) evaluate and respond to the opinions expressed by others (differentiation phase) and modify their understanding of the team based on the responses (integration phase) Leadership and team properties are represented in three experimental parameters social network structure heterogeneity of agents domains of expertise and level of their mutual interest Participative leadership is represented by a fully connected network while Leader-Member exchange (LMX) is represented by a fully connected network of in group members and several out-group members connected only to the leader Our simulation results show that in general participative leadership promotes mental model convergence better than LMX In the meantime the team performance improvement is achieved by participative leadership only when members have both heterogeneous domains of expertise and strong mutual interest In all other conditions participative leadership causes the worst degradation of team performance through team development processes while LMX is the best to minimize such team degradation Implications and suggestions for future research are provided (c) 2010 Elsevier Inc All rights reserved

    DOI

    Scopus

    110
    Citation
    (Scopus)
  • Robust Morphogenesis of Robotic Swarms [Application Notes]

    Sayama, Hiroki

    Computational Intelligence Magazine, IEEE   5 ( 3 ) 43 - 49  2010  [Refereed]

    DOI

    Scopus

    33
    Citation
    (Scopus)
  • Complex systems organizational map

    Sayama Hiroki

    http://en.wikipedia.org/wiki/File:Complex_systems_organizational_map.jpg    2010  [Refereed]

  • Adaptive Networks: An Emerging Research Theme on State-Topology Coevolution in Complex Networks

    Sayama, Hiroki

    情報処理学会研究報告. BIO, バイオ情報学   2010 ( 28 ) 1 - 3  2010  [Refereed]

  • Swarm Chemistry Evolving

    Sayama, Hiroki

    Artificial Life XII     32 - 33  2010  [Refereed]

  • Reconstructing History of Social Network Evolution Using Web Search Engines

    Akaishi, Jin, Sayama, Hiroki, Dionne, Shelley D, Chen, Xiujian, Gupta, Alka, Hao, Chanyu, Serban, Andra, Bush, Benjamin James, Head, Hadassah J, Yammarino, Francis J

    Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering   87   155 - 162  2010  [Refereed]

     View Summary

    We propose a simple web search engine based method for collecting approximated historical data of temporally changing social adaptive networks, which are rather difficult to obtain experimentally in conventional research methods. In the proposed method, a search query string is combined with additional keywords that specify inclusion/exclusion of specific years to limit the search results to a particular time point. Using the proposed method, we reconstructed the temporal evolution of a social network from 2005 to 2009 of 93 individuals who are important in the US economy. We measured centralities of those individuals for every year and found several illustrative cases where the temporal change of centrality of an individual correctly captured the actual events that are related to him/her over this time period. These results indicate the effectiveness of the proposed method. Limitations and future directions of research are discussed. © 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering.

    DOI

    Scopus

  • An Artificial Life View to the Collatz Problem.

    Hiroki Sayama

    Artificial Life XII: Proceedings of the Twelfth International Conference on the Synthesis and Simulation of Living Systems, Odense, Denmark, August 19-23, 2010     411 - 412  2010  [Refereed]

  • An Algorithm for Automatically Discovering Dynamical Rules of Adaptive Network Evolution from Empirical Data.

    Hiroki Sayama

    Bio-Inspired Models of Network, Information, and Computing Systems - 5th International ICST Conference, BIONETICS 2010, Boston, MA, USA, December 1-3, 2010, Revised Selected Papers     497 - 504  2010  [Refereed]

    DOI

    Scopus

    2
    Citation
    (Scopus)
  • Swarm intelligence

    Birattari, Mauro, Di Caro, Gianni A, Doursat, Ren{\'e}, Engelbrecht, Andries P, Floreano, Dario, Gambardella, Luca Maria, Gro{\ss}, Roderich, Sahin, Erol, St{\"u}tzle, Thomas, Sayama, Hiroki

       2010

  • Teaching Social Complexity and Multidisciplinary Team Building: An Experimental Engineering Approach

    Laramee Craig, Dionne Shelley, Sayama Hiroki, Wilson David

    American Society for Engineering Education    2009  [Refereed]

  • Generative network automata: A generalized framework for modeling adaptive network dynamics using graph rewritings

    Sayama, Hiroki, Laramee, Craig

    Adaptive Networks     311 - 332  2009  [Refereed]

     View Summary

    A variety of modeling frameworks have been proposed and utilized in complex
    systems studies, including dynamical systems models that describe state
    transitions on a system of fixed topology, and self-organizing network models
    that describe topological transformations of a network with little attention
    paid to dynamical state changes. Earlier network models typically assumed that
    topological transformations are caused by exogenous factors, such as
    preferential attachment of new nodes and stochastic or targeted removal of
    existing nodes. However, many real-world complex systems exhibit both of these
    two dynamics simultaneously, and they evolve largely autonomously based on the
    system's own states and topologies. Here we show that, by using the concept of
    graph rewriting, both state transitions and autonomous topology transformations
    of complex systems can be seamlessly integrated and represented in a unified
    computational framework.We call this novel modeling framework "Generative
    Network Automata (GNA)". In this chapter, we introduce basic concepts of GNA,
    its working definition, its generality to represent other dynamical systems
    models, and some of our latest results of extensive computational experiments
    that exhaustively swept over possible rewriting rules of simple binary-state
    GNA. The results revealed several distinct types of the GNA dynamics.

    DOI

    Scopus

    19
    Citation
    (Scopus)
  • Swarm chemistry

    Sayama, Hiroki

    Artificial Life   15 ( 1 ) 105 - 114  2009  [Refereed]  [International journal]

     View Summary

    We propose swarm chemistry a new artificial chemistry framework that uses artificial swarm populations as chemical reactants. Reaction in swarm chemistry is not determined by predefined reaction rules as commonly assumed in typical artificial chemistry studies, but is spontaneously achieved by the emergence of a new spatiotemporal pattern of collective behavior through the kinetic interaction between multiple chemical species. We developed a prototype of an interactive simulation tool with which one can explore the dynamics of swarm chemistry using an interactive evolutionary method. Several preliminary results are reported to illustrate the characteristics and effectiveness of this framework, including spontaneous segregation of distinct chemical species, production and restriction of movements, and interactive design of complex biological-looking structures.

    DOI PubMed

    Scopus

    75
    Citation
    (Scopus)
  • Enhancing the architecture of interactive evolutionary design for exploring heterogeneous particle swarm dynamics: An in-class experiment.

    Hiroki Sayama, Shelley D. Dionne, Craig B. Laramee, David Sloan Wilson

    2009 IEEE SYMPOSIUM ON ARTIFICIAL LIFE     85 - 91  2009  [Refereed]

     View Summary

    We developed Swarm Chemistry 1.2, a new version of the Swarm Chemistry simulator with an enhanced architecture of interactive evolutionary design for exploring heterogeneous self-propelled particle swarm dynamics. In the new version, each evolutionary operator acts locally and visually to part of the population of swarms on a screen, without causing entire generation changes that were used in earlier versions. This new architecture is intended to represent cognitive actions in human thinking and decision making processes more naturally. We tested the effectiveness of the new architecture through an in-class experiment with college students participating as designers as well as evaluators of swarms. We also measured the effects of mixing and mutation operators to the performance improvement of the design processes. The students' responses showed that the designs produced using the new version received significantly higher ratings from students than those produced using the old one, and also that each of the mixing and mutation operators contributed nearly independently to the improvement of the design quality. These results demonstrate the effectiveness of the new architecture of interactive evolutionary design, as well as the importance of having diverse options of action (i.e., multiple evolutionary operators in this context) in iterative design and decision making processes. This work also presents one of the few examples of human-involved experiments on the statistical evaluation of artificial lifeforms, whose quality (such as "livingness") would be hard to assess without using human cognition at this point.

    DOI

    Scopus

    10
    Citation
    (Scopus)
  • Cultural transmission in robotic swarms through RFID cards.

    Joshua Brandoff, Hiroki Sayama

    2009 IEEE SYMPOSIUM ON ARTIFICIAL LIFE     171 - 178  2009  [Refereed]

     View Summary

    The recent development of economical high-capacity RFID cards has opened up a new opportunity for stigmergic robotic swarms. Through these cards, robotic agents can dynamically exchange more complex, logical information, such as the whole set of their behavioral rules or "culture". To the best of our knowledge, this opportunity has not been explored in swarm robotics and other collective robotics communities. We have developed a prototypical robotic swarm system comprised of 8 low-cost OPEN-ROBOTs with the ability to avoid obstacles and exchange information with low-capacity RFID cards randomly distributed in an environment. To evaluate the effectiveness of our RFID-based cultural transmission technique, we created a realistic computer simulation to test the swarm's competence in mapping a virtual multi-room house covered with 80 low-capacity RFID cards in under one hour. By increasing the probability that a robot adopts a random exploration behavior different from one "marked" on a card, the swarm is able to cover more of an environment with higher consistency between trials. This result indicates that encouraging diversity among agents supports robust emergent behavior and lays the groundwork for future experiments with higher-capacity RFID cards.

    DOI

    Scopus

    1
    Citation
    (Scopus)
  • Adaptive networks

    Gross, Thilo, Sayama, Hiroki

    Adaptive Networks    2009

  • Effect of sensory blind zones on milling behavior in a dynamic self-propelled particle model.

    Jonathan P Newman, Hiroki Sayama

    Physical review. E, Statistical, nonlinear, and soft matter physics   78 ( 1 Pt 1 ) 011913 - 011913  2008.07  [Refereed]  [International journal]

     View Summary

    Emergent pattern formation in self-propelled particle (SPP) systems is extensively studied because it addresses a range of swarming phenomena that occur without leadership. Here we present a dynamic SPP model in which a sensory blind zone is introduced into each particle's zone of interaction. Using numerical simulations, we discovered that the degradation of milling patterns with increasing blind zone ranges undergoes two distinct transitions, including a spatially non-homogeneous transition that involves cessation of particles' motion caused by broken symmetries in the interaction fields. Our results also show the necessity of nearly complete panoramic sensory ability for milling behavior to emerge in dynamic SPP models, suggesting a possible relationship between collective behavior and the sensory systems of biological organisms.

    DOI PubMed

    Scopus

    25
    Citation
    (Scopus)
  • Effect of sensory blind zones on milling behavior in a dynamic self-propelled particle model

    Newman, Jonathan P, Sayama, Hiroki

    Physical Review E   78 ( 1 ) 011913 - 011913  2008  [Refereed]

     View Summary

    Emergent pattern formation in self-propelled particle (SPP) systems is extensively studied because it addresses a range of swarming phenomena that occur without leadership. Here we present a dynamic SPP model in which a sensory blind zone is introduced into each particle's zone of interaction. Using numerical simulations, we discovered that the degradation of milling patterns with increasing blind zone ranges undergoes two distinct transitions, including a spatially non-homogeneous transition that involves cessation of particles' motion caused by broken symmetries in the interaction fields. Our results also show the necessity of nearly complete panoramic sensory ability for milling behavior to emerge in dynamic SPP models, suggesting a possible relationship between collective behavior and the sensory systems of biological organisms.

    DOI

    Scopus

    25
    Citation
    (Scopus)
  • Construction theory, self-replication, and the halting problem

    Sayama, Hiroki

    Complexity   13 ( 5 ) 16 - 22  2008  [Refereed]

     View Summary

    This essay aims to propose construction theory, a new domain of theoretical
    research on machine construction, and use it to shed light on a fundamental
    relationship between living and computational systems. Specifically, we argue
    that self-replication of von Neumann's universal constructors holds a close
    similarity to circular computational processes of universal computers that
    appear in Turing's original proof of the undecidability of the halting problem.
    The result indicates the possibility of reinterpreting a self-replicating
    biological organism as embodying an attempt to solve the halting problem for a
    {\em diagonal} input in the context of construction. This attempt will never be
    completed because of the indefinite cascade of self-computation/construction,
    which accounts for the undecidability of the halting problem and also agrees
    well with the fact that life has maintained its reproductive activity for an
    indefinitely long period of time.

    DOI

    Scopus

    5
    Citation
    (Scopus)
  • Self-organizing heterogeneous swarms designed through evolutionary methods.

    Hiroki Sayama

    Artificial Life XI: Proceedingshe of the Eleventh International Conference on the Synthesis and Simulation of Living Systems, Winchester, United Kingdom, August 5-8, 2008     801 - 801  2008  [Refereed]

  • Evolution in spatial predator--prey models and the “prudent predator”: The inadequacy of steady-state organism fitness and the concept of individual and group selection

    Goodnight, C, Rauch, E, Sayama, H, De Aguiar, MAM, Baranger, M, Bar-yam, Y

    Complexity   13 ( 5 ) 23 - 44  2008  [Refereed]

     View Summary

    We review recent research which reveals: (1) how spatially distributed populations avoid overexploiting resources due to the local extinction of over-exploitative variants, and (2) how the conventional understanding of evolutionary processes is violated by spatial populations so that basic concepts, including fitness assignment to individual organisms, are not applicable, and even kin and group selection are unable to describe the mechanism by which exploitative behavior is bounded. To understand these evolutionary processes, a broader view is needed of the properties of multiscale spatiotemporal patterns in organism-environment interactions. We discuss measures that quantify the effects of these interactions on the evolution of a population, including multigenerational fitness and the heritability of the environment. (c) 2008 Wiley Periodicals, Inc.

    DOI

    Scopus

    33
    Citation
    (Scopus)
  • Construction theory, self-replication, and the halting problem.

    Hiroki Sayama

    Complex.   13 ( 5 ) 16 - 22  2008  [Refereed]

     View Summary

    This essay aims to propose construction theory, a new domain of theoretical research on machine construction, and use it to shed light on a fundamental relationship between living and computational systems. Specifically, we argue that self-replication of von Neumann's universal constructors holds a close similarity to circular computational processes of universal computers that appear in Turing's original proof of the undecidability of the halting problem. The result indicates the possibility of reinterpreting a self-replicating biological organism as embodying an attempt to solve the halting problem for a diagonal input in the context of construction. This attempt will never be completed because of the indefinite cascade of self-computation/construction, which accounts for the undecidability of the halting problem and also agrees well with the fact that life has maintained its reproductive activity for an indefinitely long period of time. (c) 2008 Wiley Periodicals, Inc.

    DOI

    Scopus

    5
    Citation
    (Scopus)
  • A complex systems perspective on collaborative design

    Mark Klein, Hiroki Sayama, Peyman Faratin, Yaneer Bar-Yam

    UNIFYING THEMES IN COMPLEX SYSTEMS IV   4   3 - +  2008  [Refereed]

    DOI

  • Spontaneous Pattern Formation and Diversity in Spatially Structured Evolutionary Ecology

    Sayama, Hiroki, Kaufman, Les, Bar-Yam, Yaneer

    Ecology Research Trends     231 - 231  2007  [Refereed]

  • Evolutionary perspective on collective decision making

    Farrell Dene, Sayama Hiroki, Dionne Shelley, Yammarino Francis, Wilson David Sloan

    Proceedings of the Seventh International Conference on Complex Systems (ICCS 2007)    2007  [Refereed]

    CiNii

  • Generative Network Automata: A Generalized Framework for Modeling Complex Dynamical Systems with Autonomously Varying Topologies.

    Hiroki Sayama

    2007 IEEE SYMPOSIUM ON ARTIFICIAL LIFE     214 - 221  2007  [Refereed]

     View Summary

    We propose a new modeling framework "Generative Network Automata (GNA)" that can uniformly describe both state transitions and autonomous topology transformations of complex dynamical networks. GNA is formulated as an extension of existing complex dynamical network models to include a new set of generative update rules that determine how local network topologies will change based on the current local network states and topologies. This paper introduces basic concepts of GNA, its formal definitions, its generality to represent other dynamical systems models, and some preliminary results of an exhaustive sweep of possible dynamics found in elementary binary GNA with restricted updating rules.

    DOI

    Scopus

    19
    Citation
    (Scopus)
  • Decentralized Control and Interactive Design Methods for Large-Scale Heterogeneous Self-Organizing Swarms.

    Hiroki Sayama

    ADVANCES IN ARTIFICIAL LIFE, PROCEEDINGS   4648   675 - 684  2007  [Refereed]

     View Summary

    We present new methods of decentralized control and interactive design for artificial swarms of a large number of agents that can spontaneously organize and maintain non-trivial heterogeneous formations. Our model assumes no elaborate sensing, computation, or communication capabilities for each agent; the self-organization is achieved solely by simple kinetic interactions among agents. Specifications of the final formations are indirectly and. implicitly woven into a list of different kinetic parameter settings and their proportions, which would be hard to obtain with a conventional top-down design method but may be designed heuristically through interactive design processes.

    DOI

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    20
    Citation
    (Scopus)
  • Visualizing evolutionary dynamics of self-replicators: A graph-based approach

    Salzberg, Chris, Antony, Antony, Sayama, Hiroki

    Artificial Life   12 ( 2 ) 275 - 287  2006  [Refereed]

     View Summary

    We present a general approach for evaluating and visualizing evolutionary dynamics of self-replicators using a graph-based representation for genealogy. Through a transformation from the space of species and mutations to the space of nodes and links, evolutionary dynamics are understood as a flow in graph space. A formalism is introduced to quantify such genealogical flows in terms of the complete history of localized evolutionary events recorded at the finest level of detail. Represented in a multidimensional viewing space, collective dynamical properties of an evolving genealogy are characterized in the form of aggregate flows. We demonstrate the effectiveness of this approach by using it to compare the evolutionary exploration behavior of self-replicating loops under two different environmental settings. © 2006 Massachusetts Institute of Technology.

    DOI PubMed

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    3
    Citation
    (Scopus)
  • On self-replication and the halting problem

    Sayama, Hiroki

    arXiv preprint nlin/0603026    2006  [Refereed]

  • Wriggraph: A Kinetic Graph Model That Uniformly Describes Ontogeny and Motility of Artificial Creatures

    Sano Koji, Hiroki Sayama, Hiroki

    Artificial life X: proceedings of the Tenth International Conference on the Simulation and Synthesis of Living Systems   10   77  2006  [Refereed]

  • Self-replicating machines attempting to solve the unsolvable

    Sayama Hiroki

    Workshop on Machine Self-Replication, Tenth International Conference on the Simulation and Synthesis of Living Systems (ALife X)    2006  [Refereed]

  • Using RFID and a Low Cost Robot to Evolve Foraging Behavior

    Howell Abe, McGrann Roy, Eckert Richard, Sayama Hiroki, Way Eileen

    Late Breaking Paper of the 2006 Genetic and Evolutionary Computation Conference    2006  [Refereed]

  • Teaching emergence and evolution simultaneously through simulated breeding of artificial swarm behaviors

    Sayama Hiroki

    Proceedings of the Sixth International Conference on Complex Systems (ICCS2006). Cambridge, MA: NECSI. Available online at http://necsi. org/events/iccs6/proceedings. html    2006  [Refereed]

  • The role of spontaneous pattern formation in the creation and maintenance of biological diversity

    Sayama, Hiroki, Kaufman, Les, Bar-Yam, Yaneer

    Unifying Themes in Complex Systems     307 - 314  2006  [Refereed]

  • The dynamics of collaborative design: insights from complex systems and negotiation research

    Klein, Mark, Sayama, Hiroki, Faratin, Peyman, Bar-Yam, Yaneer

    Complex Engineered Systems   2006   158 - 174  2006  [Refereed]

     View Summary

    Almost all complex artifacts nowadays, including physical artifacts such as airplanes, as well as informational artifacts such as software, organizations, business processes and so on, are defined via the interaction of many, sometimes thousands of participants, working on different elements of the design. This collaborative design process is challenging because strong interdependencies between design decisions make it difficult to converge on a single design that satisfies these dependencies and is acceptable to all participants. Current collaborative design approaches are as a result typically characterized by heavy reliance on expensive and time-consuming processes, poor incorporation of some important design concerns (typically later lifecycle issues such as environmental impact), as well as reduced creativity due to the tendency to incrementally modify known successful designs rather than explore radically different and potentially superior ones. © 2006 Springer.

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  • A Complex Systems Approach to Professional Skills Assessment in Education

    Sichtig, Heike, Laramee, Craig, Sayama, Hiroki

       2006  [Refereed]

  • An annealing protocol for negotiating complex contracts

    Klein, Mark, Faratin, Peyman, Sayama, Hiroki, Bar-Yam, Yaneer

    Handbook of Research on Nature Inspired Computing for Economics and Management   2  2006  [Refereed]

  • Negotiation algorithms for collaborative design settings

    Klein, Mark, Faratin, Peyman, Sayama, Hiroki, Bar-Yam, Yaneer

    Complex Engineered Systems     246 - 261  2006  [Refereed]

     View Summary

    Work to date on computational models of negotiation has focused almost exclusively on defining agreements consisting of one or a few independent issues. The negotiation involved in collaborative design, by contrast, is much more complex, consisting of multiple inter-dependent issues and intractably large design spaces. This paper describes a simulated annealing based approach appropriate for collaborative design negotiations that achieves near-optimal outcomes with binary issue dependencies.

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  • Formalizing the gene centered view of evolution

    Bar-Yam, Yaneer, Sayama, Hiroki

    Unifying Themes in Complex Systems     215 - 222  2006  [Refereed]

  • Visualizing evolutionary dynamics of self-replicators: A graph-based approach

    Salzberg, Chris, Antony, Antony, Sayama, Hiroki

    Artificial Life   12 ( 2 ) 275 - 287  2006  [Refereed]  [International journal]

     View Summary

    We present a general approach for evaluating and visualizing evolutionary dynamics of self-replicators using a graph-based representation for genealogy. Through a transformation from the space of species and mutations to the space of nodes and links, evolutionary dynamics are understood as a flow in graph space. A formalism is introduced to quantify such genealogical flows in terms of the complete history of localized evolutionary events recorded at the finest level of detail. Represented in a multidimensional viewing space, collective dynamical properties of an evolving genealogy are characterized in the form of aggregate flows. We demonstrate the effectiveness of this approach by using it to compare the evolutionary exploration behavior of self-replicating loops under two different environmental settings.

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    3
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  • BisNet: An Information Sharing System Using Bookmarks of Web Browsers

    Sano, Koji, Sayama, Hiroki

    Transactions of the Japanese Society for Artificial Intelligence   20 ( 4 ) 281 - 288  2005  [Refereed]

     View Summary

    We propose a new information sharing system, named "BisNet", which automatically gathers information about the bookmarks stored in users' web browsers and helps the users exchange URIs of possibly interesting web pages with others who have similar interest with them. Being different from other typical agent services that gather and provide information according to pre-registered user profiles, BisNet is expected to share more relevant information because of its use of web browser bookmarks that are actively selected and ordered by many humans. To enhance the relevance of information being shared, we developed a novel algorithm for directory evaluation. This algorithm only looks at the local referential structure between bookmark directories and URIs and calculates for each directory the "order index" that represents how well its content URIs are put in order with a focus on specific areas of interest. Then each directory receives new URIs from other related directories with large order indexes. The repetition of such URI exchanges makes the whole directory-URI networks dynamically form directory groups according to the commonness of the URIs they refer to. Our method is unique in that it pays no attention to the actual contents of web pages, and thus is much simpler and faster than other methods based on the result of content analysis. We carried out a field trial that involved 45 people who used a prototype version of BisNet clients. The result indicated that the relevance of shared URIs positively correlated with the "order index" of surrounding related directories, demonstrating the effectiveness of the method we proposed.

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    8
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  • Playing a 3D Game of Life in an Interactive Virtual Sandbox

    Ogihara, Daisuke, Sayama, Hiroki

    Advances in Artificial Life   3630   481 - 490  2005  [Refereed]

     View Summary

    We propose a novel artificial-life-oriented media art "RomperSand", which applies a three-dimensional version of the Game of Life (GoL) CA for the construction of an interactive virtual playground. In RomperSand, two distinct sets of state-transition rules are combined together: one for simulating physically plausible motion of virtual sand particles and the other for realizing the GoL-like dynamic behavior of living structures. Players can operate several virtual tools to create, destroy, and interact with these structures. The system was implemented as a Windows application and was tested by several users, gaining positive appreciations from them.

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  • MASSE: environment supporting for simulation and analysis of multiagent systems.

    Tomomi Takashina, Zhenbo Bi, Ariuna Damba, Guilan Zhi, Kazuhide Tanaka, Hiroki Sayama, Shigeyoshi Watanabe

    2005 INTERNATIONAL SYMPOSIUM ON COLLABORATIVE TECHNOLOGIES AND SYSTEMS, PROCEEDINGS     203 - 209  2005  [Refereed]

     View Summary

    In multiagent system research, the work in building simulation model and the effort in developing analysis methods are closely related because building multiagent models relies heavily on new effective analysis methods while justifying new analysis methods needs the simulation results of multiagent models. MASSE(Multiagent Simulation Systematic Explorer) was proposed as an integrated environment which is aimed at (a) to conduct efficient simulation by intelligent scheduling, (b) to conduct intelligent data analysis and knowledge discovery on simulation data, and (c) to develop such analysis methods themselves. Current implementation of MASSE is described in this manuscript, and its usefulness is shown in three aspects: simple accommodation of existing simulators, satisfactory performance for adopting grid computing technique, and systematic data analysis tool. Collaboration among simulation developers and analysts can be strongly supported by using MASSE to incorporate various simulators and unified method for data analysis. We conclude that the current implementation of MASSE is satisfactory.

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  • 生きている表面

    Hiroki Sayama

    芸術科学会論文誌   3 ( 3 ) 193 - 196  2004  [Refereed]

     View Summary

    In this paper we describe a concept of animated texture using A-life model called "evoloop." The texture transforms interactively according to the input by image recognition. We created an interactive art <living surfaces> using this technique. <Living Surfaces> is an interactive art realizing dynamic transformations of animated textures. On the square canvas, a complicated computer-generated color abstract image is projected, dynamically changing when people move their bodies or small black geometric shapes on it. The evolving patterns generated by "evoloop" appear according to the position of the black shapes. On the rectangle canvas, a three-dimensional creature image is projected, the texture of which reflects the pattern generated on the square canvas.

    DOI CiNii

  • A tangled hierarchy of graph-constructing graphs

    C Salzberg, H Sayama, T Ikegami

    Artificial Life IX     495 - 500  2004  [Refereed]

     View Summary

    The traditional construction paradigm of machine and tape is reformulated in a functionally homogeneous space of directed graph structures. Hierarchy-based roles, normally appointed to actors in a construction process, are dissolved and replaced by symmetric, level-less engagement. The separation between static (information carrying) and active (information processing) structures, imposed by mandate of the rules or physics in earlier theoretical models, results instead purely from graph topology. While encompassing traditional machine-tape paradigms as a special case, the formalism is shown to incorporate a wider class of construction relations. Exploiting its flexibility, a representation of a Turing machine is demonstrated, establishing computation universality. The concept of a "Tangled Construction Hierarchy" is introduced.

  • A Complex Systems Perspective on Collaborative Design

    Klein, Mark, Faratin, Peyman, Sayama, Hiroki, Bar-Yam, Yaneer

    An Application Science for Multi-Agent Systems     77 - 93  2004  [Refereed]

  • Evolutionary dynamics of cellular automata-based self-replicators in hostile environments

    Salzberg, Chris, Antony, Antony, Sayama, Hiroki

    BioSystems   78 ( 1-3 ) 119 - 134  2004  [Refereed]  [International journal]

     View Summary

    In this paper we investigate population dynamics, genealogy and complexity-increase of locally interacting populations of cellular automata-based evolving self-replicating loops (evoloops). We outline experiments indicating that the evolutionary growth in complexity, known to be achievable in principle given the complete genetic accessibility granted by universal construction, may be achievable in practice using much simpler replicating structures. By introducing evoloop populations to hostile environments, we demonstrate that selection pressures toward smaller species can be mediated to enable evolutionary accessibility to larger species, which themselves roam a much more vast portion of genetic state-space. We show that this growth in size results from intrinsically biased genealogy inherent in the rules of the evoloop CA, normally suppressed by selection pressures from direct competition favouring the smallest species. This shows that, in populations of simple self-replicating structures, a limited form of complexity-increase may result from a process which is driven by biased genealogical connectivity--a purely emergent property arising out of bottom-up evolutionary dynamics--and not just by adaptation . Implications of this result are discussed and contrasted with other self-replication studies in Artificial Life and Biology.

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    9
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  • Complex genetic evolution of self-replicating loops

    C Salzberg, A Antony, H Sayama

    Artificial Life IX     262 - 267  2004  [Refereed]

     View Summary

    It is generally believed that self-replication models constructed on cellular automata have quite limited evolutionary dynamics in both diversity and adaptative behavior. Contrary to this view, we show that complex genetic diversification and adaptation processes may occur in self-replicating loop populations. Applying newly developed tools for detailed genetic identification and genealogy tracing to evoloop populations, we uncovered a genotypic permutation space that expands combinatorially with replicator size. Within this space populations demonstrate broad behavioral diversity and non-trivial genetic adaptation, maximizing colony density while enhancing sustainability against other species. We also found a set of non-mutable subsequences enabling genetic operations that alter fitness differentials and promote long-term evolutionary exploration. These results reveal the amazing potential of cellular automata to re-create complex genetic evolution of self-replicators in a simple, deterministic framework.

  • Self-protection and diversity in self-replicating cellular automata

    Sayama, Hiroki

    Artificial Life   10 ( 1 ) 83 - 98  2004  [Refereed]  [International journal]

     View Summary

    The concept of self-protection, a capability of an organism to protect itself from exogenous attacks, is introduced into the design of artificial evolutionary systems as a possible method to create and maintain diversity in the population. Three different mechanisms of self-protection are considered and implemented on a cellular-automaton-based evolutionary system, the evoloop. Simulation results imply a positive effect of those mechanisms on diversity maintenance, especially when the self-protection is moderate so that it conserves both the attacker and the attacked. This letter briefly reports the models and the simulation results obtained using those models.

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    14
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  • Heredity, Complexity, and Surprise: Embedded Self-Replication and Evolution in CA.

    Chris Salzberg, Hiroki Sayama

    CELLULAR AUTOMATA, PROCEEDINGS   3305   161 - 171  2004  [Refereed]

     View Summary

    This paper reviews the history of embedded, evolvable self-replicating structures implemented as cellular automata systems. We relate recent advances in this field to the concept of the evolutionary growth of complexity, a term introduced by McMullin to describe the central idea contained in von Neumann's self-reproducing automata theory. We show that conditions for such growth are in principle satisfied by universal constructors, yet that in practice much simpler replicators may satisfy scaled-down - yet equally relevant - versions thereof. Examples of such evolvable, self-replicators are described and discussed, and future challenges identified.

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    2
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  • Complex genetic evolution of artificial self-replicators in cellular automata

    Salzberg, Chris, Sayama, Hiroki

    Complexity   10 ( 2 ) 33 - 39  2004  [Refereed]

     View Summary

    It is widely believed that evolutionary dynamics of artificial self-replicators realized in cellular automata (CA) are limited in diversity and adaptation. Contrary to this view, we show that complex genetic evolution may occur within simple CA. The evolving self-replicating loops ("evoloops") we investigate exhibit significant diversity in macro-scale morphologies and mutational biases, undergoing nontrivial genetic adaptation by maximizing colony density and enhancing sustainability against other species. Nonmutable subsequences enable genetic operations that alter fitness differentials and promote long-term evolutionary exploration. These results demonstrate a unique example of genetic evolution hierarchically emerging from local interactions between elements much smaller than individual replicators. (c) 2004 Wiley Periodicals, Inc.

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    12
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  • 人工生命 (私のブックマーク)

    Hiroki Sayama

    人工知能学会誌   18 ( 1 ) 90  2003  [Refereed]

  • von Neumann’s machine in the shell: Enhancing the robustness of self-replication processes

    Sayama, Hiroki

    Artificial life eight   8   49 - 49  2003  [Refereed]

  • Spontaneous evolution of Self-reproducing loops On

    Sayama Hiroki

    Unifying Themes In Complex Systems, Volume 2: Proceedings Of The Second International Conference On Complex Systems   2   363  2003  [Refereed]

  • Self-protection maintains diversity of artificial self-replicators evolving in cellular automata

    H Sayama

    2003 NASA/DOD CONFERENCE ON EVOLVABLE HARDWARE     242 - 245  2003  [Refereed]

     View Summary

    The concept of "self-protection", a capability of an organism to protect itself from exogenous attacks, is introduced to the design of artificial evolutionary systems as a possible method to create and maintain diversity in the population. Three different mechanisms of setf-protection are considered and implemented on a cellular automata based evolutionary system, the evoloop. Simulation results imply a positive effect of those mechanisms on diversity maintenance, especially when the self-protection is moderate so that it conserves both the attacker and the attacked.

  • Robustness of spontaneous pattern formation in spatially distributed genetic populations

    Aguiar, MAM de, Baranger, Michel, Bar-Yam, Yaneer, Sayama, Hiroki

    Brazilian journal of physics   33 ( 3 ) 514 - 520  2003  [Refereed]

     View Summary

    Spatially distributed genetic populations that compete locally for resources and mate only with sufficiently close neighbors, may give rise to spontaneous pattern formation. Depending on the population parameters, like death rate per generation and size of the competition and mating neighborhoods, isolated groups of individuals, or demes, may appear. The existence of such groups in a population has consequences for genetic diversity and for speciation. In this paper we discuss the robustness of demes formation with respect to two important characteristics of the population: the way individuals recognize the demarcation of the local neighborhoods and the way competition for resources affects the birth rate in an overcrowed situation. Our results indicate that demes are expected to form only for sufficiently sharp demarcations and for sufficiently intense competition.

  • Spontaneous pattern formation and genetic diversity in habitats with irregular geographical features

    Sayama, Hiroki, Kaufman, Les, Bar-Yam, Yaneer

    Conservation Biology   17 ( 3 ) 893 - 900  2003  [Refereed]

     View Summary

    The role of spontaneous pattern formation, the appearance of inhomogeneities that are not directly imposed by external forces, has not been closely examined in the context of the origin and maintenance of genetic diversity in wild populations. Using individual-based computer simulations, we demonstrated that such patterns form in spatially distributed species with local demes under disruptive selection. In our model systems, spatial patterns of genetic diversity arose and changed over time even in the context of a spatially homogenous environment. The spatial distribution and dynamics of the fittest genotypes were controlled by the movement of boundaries between domains of the different genotypes. The rate of diversity decay was dramatically slower than predicted by traditional models. Therefore, spontaneous pattern formation may lead to the maintenance of genetic diversity of a species in a contiguous habitat, despite reproductive mixing. Moreover, the diversity persisted significantly longer in larger habitats and habitats with irregular geographical features. Habitat structure was intimately linked to the preservation of genetic diversity. Spontaneous pattern formation should be considered along with other spatial effects in the design of conservation areas.

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    10
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  • Masse: Multiagent Simulation Systematic Explorer

    Tomomi Takashina Bi Zhenbo Damba Ariuna Zhi, Shigeyoshi Watanabe

    Proceedings of the 2003 Forum on Information Technology (FIT-2003), Hokkaido, Japan    2003  [Refereed]

  • A simulation model of toys that self-replicate in a physical world

    Horiguchi Emi, Sayama Hiroki

    Proceedings of the 9th Emergent Systems Symposium (Summer School on Emergence 2003), Toyama, Japan     94  2003  [Refereed]

  • Genetic diversification and complex genealogy of self-replicators discovered in simple cellular automata: A preliminary report

    Salzberg, Chris, Antony, Antony, Sayama, Hiroki

    Journal of Three-dimensional Images   17 ( 4 ) 103 - 109  2003  [Refereed]

  • Masse: Multiagent simulator systematic explorer

    Takashina Tomomi, Ariuna Damba, Zhenbo Bi, Guilan Zhi, Sen Li, Sayama Hiroki, Watanabe Shigeyoshi

    Forum on Information Technologies, Proceedings    2003  [Refereed]

  • Genetic diversification and adaptation of self-replicators discovered in simple cellular automata

    Salzberg C, Antony A, Sayama H

    Proceedings of the Sixth International Conference on Humans and Computers (HC-2003)     194  2003  [Refereed]

  • A complex systems perspective on how agents can support collaborative design

    Klein, Mark, Sayama, Hiroki, Faratin, Peyman, Bar-Yam, Yaneer

    Agent Supported Cooperative Work     255 - 271  2003  [Refereed]

  • Interplay between Turing pattern formation and domain coarsening in spatially extended population models

    Sayama Hiroki, De Aguiar, Marcus AM, Bar-Yam Yaneer, Baranger Michel

    Forma    2003  [Refereed]

  • Dynamics and genealogy of strains in spatially extended host-pathogen models

    Rauch, Erik M, Sayama, Hiroki, Bar-Yam, Yaneer

    Journal of theoretical biology   221 ( 4 ) 655 - 664  2003  [Refereed]

     View Summary

    We examine the dynamics of evolution in a generic spatial model of a pathogen infecting a population of hosts, or an analogous predator-prey system. Previous studies of this model have found a range of interesting phenomena that differ from the well-mixed version. We extend these studies by examining the spatial and temporal dynamics of strains using genealogical tracing. When transmissibility can evolve by mutation, strains of intermediate transmissibility dominate even though high-transmissibility mutants have a short-term reproductive advantage. Mutant strains continually arise and grow rapidly for many generations but eventually go extinct before dominating the system. We find that, after a number of generations, the mutant pathogen characteristics strongly impact the spatial distribution of their local host environment, even when there are diverse types coexisting. Extinction is due to the depletion of susceptibles in the local environment of these mutant strains. Studies of spatial and genealogical relatedness reveal the self-organized spatial clustering of strains that enables their impact on the local environment. Thus, we find that selection acts against the high-transmissibility strains on long time-scales as a result of the feedback due to environmental change. Our study shows that averages over space or time should not be assumed to adequately describe the evolutionary dynamics of spatially distributed host-pathogen systems. (C) 2003 Elsevier Science Ltd. All rights reserved.

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    34
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  • Optimization of robustness and connectivity in complex networks

    Shargel, Benjamin, Sayama, Hiroki, Epstein, Irving R, Bar-Yam, Yaneer

    Physical review letters   90 ( 6 ) 68701 - 68701  2003  [Refereed]

     View Summary

    Scale-free networks rely on a relatively small number of highly connected nodes to achieve a high degree of interconnectivity and robustness to random failure, but suffer from a high sensitivity to directed attack. In this paper we describe a parametrized family of networks and analyze their connectivity and sensitivity, identifying a network that has an interconnectedness closer to that of a scale-free network, a robustness to attack closer to that of an exponential network, and a resistance to failure better than that of either of those networks.

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    141
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  • Negotiating complex contracts

    Klein, Mark, Faratin, Peyman, Sayama, Hiroki, Bar-Yam, Yaneer

    Group Decision and Negotiation   12 ( 2 ) 111 - 125  2003  [Refereed]

     View Summary

    Work to date on computational models of negotiation has focused almost exclusively on defining contracts consisting of one or a few independent issues and tractable contract spaces. Many real-world contracts, by contrast, are much more complex, consisting of multiple inter-dependent issues and intractably large contract spaces. This paper describes a simulated annealing based approach appropriate for negotiating such complex contracts that achieves near-optimal social welfares for negotiations with binary issue dependencies.

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    182
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  • Visualizing evolutionary dynamics of self-replicators using graph-based genealogy

    Salzberg, Chris, Antony, Antony, Sayama, Hiroki

    Advances in Artificial Life   2801   387 - 394  2003  [Refereed]

     View Summary

    We present a general method for evaluating and visualizing evolutionary dynamics of self-replicators using a graph-based representation for genealogy. Through a transformation from the space of species and mutations to the space of nodes and links, evolutionary dynamics are understood as a flow in graph space. Mapping functions are introduced to translate graph nodes to points in an n-dimensional visualization space for interpretation and analysis. Using this scheme, we evaluate the effect of a dynamic environment on a population of self-reproducing loops. Resulting images visually reveal the critical role played by genealogical graph space partitioning in the evolutionary process.

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    3
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  • The dynamics of collaborative design: insights from complex systems and negotiation research

    Klein, Mark, Sayama, Hiroki, Faratin, Peyman, Bar-Yam, Yaneer

    Concurrent Engineering   11 ( 3 ) 201 - 209  2003  [Refereed]

     View Summary

    Almost all complex artifacts nowadays, including physical artifacts such as airplanes, as well as informational artifacts such as software, organizations, business processes, plans, and schedules, are defined via the interaction of many, sometimes thousands of participants, working on different elements of the design. This collaborative design process is typically expensive and time-consuming because strong interdependencies between design decisions make it difficult to converge on a single design that satisfies these dependencies and is acceptable to all participants. Recent research from the complex systems and negotiation literatures has much to offer to the understanding of the dynamics of this process. This paper reviews some of these insights and offers suggestions for improving collaborative design.

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    84
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  • Special Issue on a Complex Systems Perspective on Concurrent Engineering

    Klein, Mark, Braha, Dan, Sayama, Hiroki, Bar-Yam, Yaneer

    Concurrent Engineering   11 ( 3 ) 163 - 163  2003  [Refereed]

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    3
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  • Self-Protection Maintains Diversity of Artificial Self-Replicators.

    Hiroki Sayama

    Proceedings - NASA/DoD Conference on Evolvable Hardware, EH   2003-   252 - 255  2003  [Refereed]

     View Summary

    The concept of »self-protection», a capability of an organism to protect itself from exogenous attacks, is introduced to the design of artificial evolutionary systems as a possible method to create and maintain diversity in the population. Three different mechanisms of self-protection are considered and implemented on a cellular automata based evolutionary system, the evoloop. Simulation results imply a positive effect of those mechanisms on diversity maintenance, especially when the self-protection is moderate so that it conserves both the attacker and the attacked.

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  • Protocols for negotiating complex contracts

    Klein, Mark, Faratin, Peyman, Sayama, Hiroki, Bar-Yam, Yaneer

    Intelligent Systems, IEEE   18 ( 6 ) 32 - 38  2003  [Refereed]

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    96
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  • Negotiation algorithms for collaborative design settings.

    Mark Klein, Peyman Faratin, Hiroki Sayama, Yaneer Bar-Yam

    CONCURRENT ENGINEERING: ENHANCED INTEROPERABLE SYSTEMS     161 - 167  2003  [Refereed]

     View Summary

    Work to date on computational models of negotiation has focused almost exclusively on defining agreements consisting of one or a few independent issues. The negotiation involved in collaborative design, by contrast, is much more complex, consisting of multiple inter-dependent issues and intractably large design spaces. This paper describes a simulated annealing based approach appropriate for collaborative design negotiations that achieves near-optimal outcomes with binary issue dependencies.

  • Stability and instability of polymorphic populations and the role of multiple breeding seasons in phase III of Wright’s shifting balance theory

    de Aguiar, MAM, Sayama, H, Rauch, E, Bar-Yam, Y, Baranger, M

    Physical Review E   65 ( 3 ) 031909 - 031909  2002  [Refereed]

     View Summary

    It is generally difficult for a large population at a fitness peak to acquire the genotypes of a higher peak, because the intermediates produced by allelic recombination between types at different peaks are of lower fitness. In his shifting-balance theory, Wright proposed that fitter genotypes could, however, become fixed in small isolated demes by means of random genetic fluctuations. These demes would then try to spread their genome to nearby demes by migration of their individuals. The resulting polymorphism, the coexistence of individuals with different genotypes, would give the invaded demes a chance to move up to a higher fitness peak. This last step of the process, namely, the invasion of lower fitness demes by higher fitness genotypes, is known as phase III of Wright&apos;s theory. Here we study the invasion process from the point of view of the stability of polymorphic populations. Invasion occurs when the polymorphic equilibrium, established at low migration rates, becomes unstable. We show that the instability threshold depends sensitively on the average number of breeding seasons of individuals. Iteroparous species (with many breeding seasons! have lower thresholds than semelparous species (with a single breeding season). By studying a particular simple model, we are able to provide analytical estimates of the migration threshold as a function of the number of breeding seasons. Once the threshold is crossed and polymorphism becomes unstable, any imbalance between the different demes is sufficient for invasion to occur. The outcome of the invasion, however, depends on many parameters, not only on fitness. Differences in fitness, site capacities, relative migration rates, and initial conditions, all contribute to determine which genotype invades successfully. Contrary to the original perspective of Wright&apos;s theory for continuous fitness improvement, our results show that both upgrading to higher fitness peaks and downgrading to lower peaks are possible.

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    4
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  • Simple negotiating agents in complex games: Emergent equilibria and dominance of strategies

    Faratin, Peyman, Klein, Mark, Sayama, Hiroki, Bar-Yam, Yaneer

    Intelligent Agents VIII   2333   367 - 376  2002  [Refereed]

     View Summary

    We present a simple model of distributed multi-agent multi-issued contract negotiation for open systems where interactions are competitive and information is private and not shared. We then investigate via simulations two different approximate optimization strategies and quantify the contribution and costs of each towards the quality of the solutions reached. To evaluate the role of knowledge the obtained results are compared to more cooperative strategies where agents share more information. Interesting social dilemmas emerge that suggest the design of incentive mechanisms.

  • Relationship between measures of fitness and time scale in evolution

    Rauch, EM, Sayama, H, Bar-Yam, Y

    Physical Review Letters   88 ( 22 ) 228101 - 228101  2002  [Refereed]

     View Summary

    The notion of fitness is central in evolutionary biology. We use a simple spatially extended predator-prey or host-pathogen model to show a generic case where the average number of offspring of an individual as a measure of fitness fails to characterize the evolutionary dynamics. Mutants with high initial reproduction ratios have lineages that eventually go extinct due to local overexploitation. We propose general quantitative measures of fitness that reflect the importance of time scale in evolutionary processes.

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  • Spontaneous pattern formation and genetic invasion in locally mating and competing populations

    Sayama, Hiroki, de Aguiar, Marcus AM, Bar-Yam, Yaneer, Baranger, Michel

    Physical Review E   65 ( 5 ) 051919 - 051919  2002  [Refereed]

     View Summary

    We present a theoretical model of evolution of spatially distributed populations in which organisms mate with and compete against each other only locally. We show using both analysis and numerical simulation that the typical dynamics of population density variation is a spontaneous formation of isolated groups due to competition for resources. The resulting spatial separation between groups strongly affects the process of genetic invasion by local reproductive mixing, and spatially inhomogeneous genetic distributions are possible in the final states. We then consider a specific version of this model in the presence of disruptive selection, favoring two fittest types against their genetic intermediates. This case can be simplified to a system that involves just two nonconserved order parameters: population density and type difference. Since the coexistence of two fittest types is unstable in this case, symmetry breaking and coarsening occur in type difference, implying eventual dominance by one type over another for finite populations. However, such coarsening patterns may be pinned by the spontaneously generated spatial separation between isolated groups. The long-term evolution of genetic composition is found to be sensitive to the ratio of the mating and competition ranges, and other parameters. Our model may provide a theoretical basis for consideration of various properties of spatially extended evolutionary processes, including spontaneous formation of subpopulations and lateral invasion of different types.

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    1
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  • Negotiating complex contracts.

    Mark Klein, Peyman Faratin, Hiroki Sayama, Yaneer Bar-Yam

    The First International Joint Conference on Autonomous Agents & Multiagent Systems, AAMAS 2002, July 15-19, 2002, Bologna, Italy, Proceedings     753 - 757  2002  [Refereed]

    DOI

  • A complex systems perspective on computer-supported collaborative design technology

    Klein, Mark, Sayama, Hiroki, Faratin, Peyman, Bar-Yam, Yaneer

    Communications of the ACM   45 ( 11 ) 27 - 31  2002  [Refereed]

  • Computer Supported Cooperative Work in Design

    Klein M, Sayama H, Faratin P, Bar-Yam Y

    The Sixth International Conference on Computer Supported Cooperative Work in Design     5  2001  [Refereed]

  • Interplay of Genetic and Actual Lifespans

    Sayama, Hiroki, Bar-Yam, Yaneer

    Physical Review Letters   86 ( 20 ) 4718 - 4718  2001  [Refereed]

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    Scopus

  • The gene centered view of evolution and symmetry breaking and pattern formation in spatially distributed evolutionary processes

    Sayama, Hiroki, Bar-Yam, Yaneer

    Nonlinear dynamics in the Life and Social Sciences (ed. by W. Sulis and I. Trofimova), IOS Press   320   360 - 382  2001  [Refereed]

     View Summary

    The gene centered view of evolution, a framework broadly used in evolutionary theory, assumes that one can assign an effective fitness directly to each allele. This avoids the conceptual and mathematical difficulties which sexual reproduction causes in treating evolutionary processes. We formalize the gene centered view as a dynamic form of the mean field approximation applied to genomic probabilities in reproduction/selection processes. We show that the predictions of the gene centered view are invalid when symmetry breaking and pattern formation occur within a population, and in particular for spatially distributed populations with local mating neighborhoods in the presence of disruptive selection. Our results have significant implications for the fundamental and practical problems of the development and persistence of genetic diversity. They are of great importance for modem efforts in conservation biology to save endangered species which have dramatically reduced genetic diversity.

  • What Complex Systems Research Can Teach Us About Collaborative Design.

    Mark Klein, Hiroki Sayama, Peyman Faratin, Yaneer Bar-Yam

    PROCEEDINGS OF THE SIXTH INTERNATIONAL CONFERENCE ON COMPUTER SUPPORTED COOPERATIVE WORK IN DESIGN     5 - 12  2001  [Refereed]

     View Summary

    Collaborative design is challenging because strong interdependencies between design issues make it difficult to converge on a single design that satisfies these dependencies and is acceptable to all participants, Complex systems research has much to offer to the understanding of these dynamics. This paper describes some insights from the complex systems perspective.

    DOI

  • Simple Negotiating Agents in Complex Games: .

    Peyman Faratin, Mark Klein, Hiroki Sayama, Yaneer Bar-Yam

    INTELLIGENT AGENTS VIII: AGENT THEORIES, ARCHITECTURES, AND LANGUAGES   2333   367 - 376  2001  [Refereed]

     View Summary

    We present a simple model of distributed multi-agent multi-issued contract negotiation for open systems where interactions are competitive and information is private and not shared. We then investigate via simulations two different approximate optimization strategies and quantify the contribution and costs of each towards the quality of the solutions reached. To evaluate the role of knowledge the obtained results are compared to more cooperative strategies where agents share more information. Interesting social dilemmas emerge that suggest the design of incentive mechanisms.

    DOI

    Scopus

    2
    Citation
    (Scopus)
  • Self-replicating worms that increase structural complexity through gene transmission

    H Sayama

    ARTIFICIAL LIFE VII     21 - 30  2000  [Refereed]

     View Summary

    A new self-replicating cellular automata (CA) model is proposed as a latest effort toward the realization of an artificial evolutionary system on CA where structural complexity of self-replicators can increase in some cases. I utilize the idea of 'shape encoding' proposed by Morita and Imai (Morita & Imai 1996b) and make the state-transition rules of the model allow organisms to transmit genetic information to others when colliding against each other. Simulations with random initial configuration demonstrate that it is possible that the average length of organisms and the average frequency of brancing per organism both increase, with decreasing self-replication fidelity, and saturate at some constant level. The saturation is caused in part by the fixation of place and shape of organisms onto particular sites. This implies the necessity of introducing some fluidity of site arrangements into the model for further development of evolutionary models using CA-like artificial media.

  • Symmetry breaking and coarsening in spatially distributed evolutionary processes including sexual reproduction and disruptive selection

    Sayama, Hiroki, Kaufman, Les, Bar-Yam, Yaneer

    Physical Review E   62 ( 5 ) 7065 - 7065  2000  [Refereed]

     View Summary

    Sexual reproduction presents significant challenges to formal treatment of
    evolutionary processes. A starting point for systematic treatments of
    ecological and evolutionary phenomena has been provided by the gene centered
    view of evolution which assigns effective fitness to each allele instead of
    each organism. The gene centered view can be formalized as a dynamic mean field
    approximation applied to genes in reproduction / selection dynamics. We show
    that the gene centered view breaks down for symmetry breaking and pattern
    formation within a population; and show that spatial distributions of organisms
    with local mating neighborhoods in the presence of disruptive selection give
    rise to such symmetry breaking and pattern formation in the genetic composition
    of local populations. Global dynamics follows conventional coarsening of
    systems with nonconserved order parameters. The results have significant
    implications for the ecology of genetic diversity and species formation.

    DOI

    Scopus

    27
    Citation
    (Scopus)
  • Langton の自己増殖ループをもとに構成した構造解消可能型自己増殖ループ

    Hiroki Sayama

    情報処理学会論文誌数理モデル化と応用 (TOM)   40 ( SIG02 (TOM1) ) 55  1999  [Refereed]

  • A structurally dissolvable self-reproducing loop implemented from Langton's self-reproducing loop

    Sayama, HIROKI

    IPSJ Transactions SIG2 (TOM1)   40 ( 2 ) 55 - 67  1999  [Refereed]

     View Summary

    The phenomenon of death, or disappearance of life, has two aspects. One is failure in the function of life and the other is dissolution of the structure of life. In order to model the latter aspect and examine the significance of it, the author has contrived a "structurally dissolvable self-reproducing (SDSR) loop"^<2)> by introducing the capability of structural dissolution into Langton's self-reproducing (SR) loop^<1)> in which deal as functional failure has already been installed. To be more specific, a dissolving state '8' was introduced into the set of states of the cellular automata (CA) used for embodying the SR loop, besides other modifications to Langton's transition rules. Through this improvement, the SDSR loop can dissolve its own structure when faced with difficult situations such as a shortage of space for self-reproduction. This mechanism (disappearance of a subsystem of the whole system) induces, for the first time, dynamically-stabel and potentially evolvable behavior into the colony of SDSR loops. In this article, we report in detail the process of implementing the SDSR loop and its behavior, and have some discussions relevant to them.

    CiNii

  • Toward the realization of an evolving ecosystem on cellular automata

    Sayama Hiroki

    Proceedings of the Fourth International Symposium on Artificial Life and Robotics (AROB 4th'99)     254 - 257  1999  [Refereed]

    CiNii

  • A new structurally dissolvable self-reproducing loop evolving in a simple cellular automata space

    Sayama, Hiroki

    Artificial Life   5 ( 4 ) 343 - 365  1999  [Refereed]

    DOI

    Scopus

    50
    Citation
    (Scopus)
  • A study of the behavior of structurally dissolvable self-reproducing loops made from Langton's self-reproducing loops

    Sayama Hiroki

    Proceedings of the 12th Annual Conference of JSAI, Tokyo, Japan   12   657 - 658  1998  [Refereed]

    CiNii

  • Langton の自己増殖ループへの構造解消機能の導入

    Hiroki Sayama

    情報処理学会研究報告. MPS, 数理モデル化と問題解決研究報告   98 ( 44 ) 7  1998  [Refereed]

  • Spontaneous evolution of self-reproducing loops implemented on cellular automata: A preliminary report

    Sayama Hiroki

    Proceedings of the Second International Conference on Complex Systems, Nashua, NH, USA   236  1998  [Refereed]

    CiNii

  • Introduction of structural dissolution into Langton's self-reproducing loop

    H Sayama

    ARTIFICIAL LIFE VI     114 - 122  1998  [Refereed]

     View Summary

    The phenomenon of death, or disappearance of life, has two aspects. One is failure in the function of life and the other is dissolution of the structure of life. In order to examine the significance of the latter aspect, the author contrived a "structurally dissolvable self reproducing (SDSR) loop" by introducing the capability of structural dissolution into Langton's self-reproducing (SR) loop in which death as functional failure has already been installed. To be more specific, a dissolving state '8' was introduced into the set of states of the CA, besides other modifications to Langton's transition rules. Through this improvement, the SDSR loop can dissolve its own structure when faced with difficult situations such as a shortage of space for self-reproduction. This mechanism (disappearance of a subsystem of the whole system) induces, for the first time, dynamically-stable and potentially evolvable behavior into the colony of SDSR loops.

  • A closer look at the evolutionary dynamics of self-reproducing cellular automata

    Antony, A, Salzberg, C, Sayama, H

    Accepted pending revisions    1998  [Refereed]

  • プログラムされた自己解体モデルによる進化システム

    Hiroki Sayama

    ファジィシステムシンポジウム講演論文集   13   319  1997  [Refereed]

  • 高速大容量情報通信環境における高精細度動画像伝送評価用映像の開発

    Hiroki Sayama

    電子情報通信学会総合大会講演論文集   1996   394 - 394  1996  [Refereed]

    CiNii

  • Artificial life based on programmed self-decomposition model

    Oohashi, Tsutomu, Sayama, Hiroki, Ueno, Osamu, Maekawa, T

       1996  [Refereed]

  • Programed Self-Decomposition Model and Artificial Life

    Oohashi, Tsutomu, Sayama, Hiroki, Osamu, UENO, Maekawa, Tadao, Self-decomposition, Programed

       1995  [Refereed]

  • A COMPUTER SIMULATION OF PROGRAMED SELF-DECOMPOSITION MODEL

    Sayama, Hiroki

       1994  [Refereed]

  • A computer simulation of programmed self-decomposition model

    Sayama Hiroki

    Proceedings of Numerical Analysis Symposium 23rd     67  1994  [Refereed]

▼display all

Books and Other Publications

  • Adaptive Networks: Theory, Models and Applications (Understanding Complex Systems)

    Thilo Gross, Hiroki Sayama

    Springer  2009.09 ISBN: 3642012833

    ASIN

  • MASSE: Environment supporting for simulation and analysis of multiagent systems

    Proceedings of the 2005 International Symposium on Collaborative Technologies and Systems (CTS 2005)  2005.05

  • MASSE: Environment supporting for simulation and analysis of multiagent systems

    Proceedings of the 2005 International Symposium on Collaborative Technologies and Systems (CTS 2005)  2005.05

  • Heredity, complexity and surprise: Embedded self-replication and evolution in CA

    Cellular Automata: Proceedings of the Sixth International Conference on Cellular Automata for Research and Industry (ACRI 2004), P. M. A. Sloot, B. Chopard, and A. G. Hoekstra, eds., Springer-Verlag  2004.10

  • Heredity, complexity and surprise: Embedded self-replication and evolution in CA

    Cellular Automata: Proceedings of the Sixth International Conference on Cellular Automata for Research and Industry (ACRI 2004), P. M. A. Sloot, B. Chopard, and A. G. Hoekstra, eds., Springer-Verlag  2004.10

  • Complex genetic evolution of self-replicating loops

    Artificial Life IX: Proceedings of the Ninth International Conference on the Simulation and Synthesis of Living Systems, J. Pollack, M. Bedau, P. Husbands, T. Ikegami, and R. A. Watson, eds., MIT Press  2004.09

  • Complex genetic evolution of self-replicating loops

    Artificial Life IX: Proceedings of the Ninth International Conference on the Simulation and Synthesis of Living Systems, J. Pollack, M. Bedau, P. Husbands, T. Ikegami, and R. A. Watson, eds., MIT Press  2004.09

  • A complex systems perspective on collaborative design

    Multi-Agent Systems: An Application Science, T. Wagner, ed., Kluwer Academic Publishers  2004

  • A complex systems perspective on collaborative design

    Multi-Agent Systems: An Application Science, T. Wagner, ed., Kluwer Academic Publishers  2004

  • マルチエージェントシステムのための実験支援環境Masseの提案

    第2回情報科学技術フォーラム(FIT-2003)講演論文集  2003.09

  • Visualizing evolutionary dynamics of self-replicators using graph-based genealogy

    Proceedings of the Seventh European Conference on Artificial Life (ECAL 2003), W. Banzhaf, T. Christaller, P. Dittrich, J. T. Kim, and J. Ziegler, eds., Dortmund, Germany, Springer-Verlag.  2003.09

  • Masse: Multiagent Simulation Systematic Explorer

    Proceedings of the 2003 Forum on Information Technology (FIT-2003), Hokkaido, Japan  2003.09

  • Visualizing evolutionary dynamics of self-replicators using graph-based genealogy

    Proceedings of the Seventh European Conference on Artificial Life (ECAL 2003), W. Banzhaf, T. Christaller, P. Dittrich, J. T. Kim, and J. Ziegler, eds., Dortmund, Germany, Springer-Verlag.  2003.09

  • Genetic diversification and adaptation of self-replicators discovered in simple cellular automata

    Proceedings of the Sixth International Conference on Humans and Computers (HC-2003), University of Aizu, Japan  2003.08

  • Genetic diversification and adaptation of self-replicators discovered in simple cellular automata

    Proceedings of the Sixth International Conference on Humans and Computers (HC-2003), University of Aizu, Japan  2003.08

  • Negotiation algorithms for collaborative design settings

    Proceedings of the 10th ISPE International Conference on Concurrent Engineering: Research and Applications (CE 2003), Madeira Island, Portugal  2003.07

  • Self-protection maintains diversity of artificial self-replicators evolving in cellular automata

    Proceedings of the 2003 NASA/DoD Conference on Evolvable Hardware (EH2003), J. Lohn, R. Zebulum, J. Steincamp, D. Keymeulen, A. Stoica, and M. I. Ferguson, eds, Chicago, Illinois, IEEE Press  2003.07

  • Negotiation algorithms for collaborative design settings

    Proceedings of the 10th ISPE International Conference on Concurrent Engineering: Research and Applications (CE 2003), Madeira Island, Portugal  2003.07

  • Self-protection maintains diversity of artificial self-replicators evolving in cellular automata

    Proceedings of the 2003 NASA/DoD Conference on Evolvable Hardware (EH2003), J. Lohn, R. Zebulum, J. Steincamp, D. Keymeulen, A. Stoica, and M. I. Ferguson, eds, Chicago, Illinois, IEEE Press  2003.07

  • A complex systems perspective on how agents can support collaborative design

    Agent Supported Cooperative Work, Y. Ye and E. Churchill, eds., Kluwer Academic Publishers  2003.03

  • A complex systems perspective on how agents can support collaborative design

    Agent Supported Cooperative Work, Y. Ye and E. Churchill, eds., Kluwer Academic Publishers  2003.03

  • Workplace construction: A theoretical model of robust self-replication in kinematic universe

    Proceedings of the Eighth International Symposium on Artificial Life and Robotics (AROB 8th 2003), M. Sugisaka and H. Tanaka, eds.  2003.01

  • Workplace construction: A theoretical model of robust self-replication in kinematic universe

    Proceedings of the Eighth International Symposium on Artificial Life and Robotics (AROB 8th 2003), M. Sugisaka and H. Tanaka, eds.  2003.01

  • Von Neumann's machine in the shell: Enhancing the robustness of self-replication processes

    Artificial Life VIII: Proceedings of the Eighth International Conference on Artificial Life, R. K. Standish, M. A. Bedau, and H. A. Abbass, eds., MIT Press  2002.12

  • Von Neumann's machine in the shell: Enhancing the robustness of self-replication processes

    Artificial Life VIII: Proceedings of the Eighth International Conference on Artificial Life, R. K. Standish, M. A. Bedau, and H. A. Abbass, eds., MIT Press  2002.12

  • Toward the physical implementation of artificial self-replicating and evolving systems

    Proceedings of the International Workshop on Modern Science and Technology 2002, University of Electro-Communications, Tokyo, Japan  2002.09

  • Toward the physical implementation of artificial self-replicating and evolving systems

    Proceedings of the International Workshop on Modern Science and Technology 2002, University of Electro-Communications, Tokyo, Japan  2002.09

  • A complex systems perspective on how agents can support collaborative design

    Proceedings of the Workshop on Agents in Design (WAID'02), Cambridge, Massachusetts  2002.08

  • A complex systems perspective on how agents can support collaborative design

    Proceedings of the Workshop on Agents in Design (WAID'02), Cambridge, Massachusetts  2002.08

  • Negotiating complex contracts

    Proceedings of the First International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS-2002), AAAI Press  2002.07

  • Negotiating complex contracts

    Proceedings of the First International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS-2002), AAAI Press  2002.07

  • Breakdown of the gene-centered view: What is beyond Neo-Darwinian evolution?

    Proceedings of the Fourth International Conference on Complex Systems / InterJournal (http://interjournal.org/)  2002.06

  • Breakdown of the gene-centered view: What is beyond Neo-Darwinian evolution?

    Proceedings of the Fourth International Conference on Complex Systems / InterJournal (http://interjournal.org/)  2002.06

  • Negotiating complex contracts

    Proceedings of the AAAI Fall 2001 Symposium on Negotiation Methods for Autonomous Cooperative Systems / ROMA Working Paper ROMA-WP-2001-01, Massachusetts Institute of Technology  2001.11

  • Negotiating complex contracts

    Proceedings of the AAAI Fall 2001 Symposium on Negotiation Methods for Autonomous Cooperative Systems / ROMA Working Paper ROMA-WP-2001-01, Massachusetts Institute of Technology  2001.11

  • Simple negotiating agents in complex games: Emergent equilibria and dominance of strategies

    Proceedings of the Eighth International Workshop on Agent Theories, Architectures, and Languages (ATAL-2001) (also included in Intelligent Agent VIII: Agent Theories, Architectures, and Languages, Lecture Notes in Artificial Intelligence 2333, 367-377,・・・  2001.08

     View Summary

    Proceedings of the Eighth International Workshop on Agent Theories, Architectures, and Languages (ATAL-2001)
    (also included in Intelligent Agent VIII: Agent Theories, Architectures, and Languages, Lecture Notes in Artificial Intelligence 2333, 367-377, Springer-Verlag, 2002)

  • Simple negotiating agents in complex games: Emergent equilibria and dominance of strategies

    Proceedings of the Eighth International Workshop on Agent Theories, Architectures, and Languages (ATAL-2001) (also included in Intelligent Agent VIII: Agent Theories, Architectures, and Languages, Lecture Notes in Artificial Intelligence 2333, 367-377,・・・  2001.08

     View Summary

    Proceedings of the Eighth International Workshop on Agent Theories, Architectures, and Languages (ATAL-2001)
    (also included in Intelligent Agent VIII: Agent Theories, Architectures, and Languages, Lecture Notes in Artificial Intelligence 2333, 367-377, Springer-Verlag, 2002)

  • What complex systems research can teach us about collaborative design

    Proceedings of the Sixth International Conference on Computer Supported Cooperative Work in Design (CSCWD-2001), IEEE Press  2001.07

  • What complex systems research can teach us about collaborative design

    Proceedings of the Sixth International Conference on Computer Supported Cooperative Work in Design (CSCWD-2001), IEEE Press  2001.07

  • 計算物理学のうち数項目(セルオートマトン,自己増殖機械,自己触媒系)

    物理学辞典3訂版(培風館)  2001.04

  • The gene centered view of evolution and symmetry breaking and pattern formation in spatially distributed evolutionary processes

    Nonlinear Dynamics in the Life and Social Sciences, W. Sulis and I. Trofimova, eds., NATO Science Series, IOS Press  2001.01

  • The gene centered view of evolution and symmetry breaking and pattern formation in spatially distributed evolutionary processes

    Nonlinear Dynamics in the Life and Social Sciences, W. Sulis and I. Trofimova, eds., NATO Science Series, IOS Press  2001.01

  • Self-replicating worms that increase structural complexity through gene transmission

    Artificial Life VII: Proceedings of the Seventh International Conference on Artificial Life, M. A. Bedau, J. S. McCaskill, N. H. Packard and S. Rasmussen, eds., MIT Press  2000.08

  • Self-replicating worms that increase structural complexity through gene transmission

    Artificial Life VII: Proceedings of the Seventh International Conference on Artificial Life, M. A. Bedau, J. S. McCaskill, N. H. Packard and S. Rasmussen, eds., MIT Press  2000.08

  • Formalizing the gene centered view of evolution

    Proceedings of the Third International Conference on Complex Systems / InterJournal (http://interjournal.org/)  2000.05

  • The role of spontaneous pattern formation in the creation and maintenance of biological diversity

    Proceedings of the Third International Conference on Complex Systems / InterJournal (http://interjournal.org/)  2000.05

  • Formalizing the gene centered view of evolution

    Proceedings of the Third International Conference on Complex Systems / InterJournal (http://interjournal.org/)  2000.05

  • The role of spontaneous pattern formation in the creation and maintenance of biological diversity

    Proceedings of the Third International Conference on Complex Systems / InterJournal (http://interjournal.org/)  2000.05

  • Toward the realization of an evolving ecosystem on cellular automata

    Proceedings of the Fourth International Symposium on Artificial Life and Robotics (AROB 4th '99), M. Sugisaka and H. Tanaka, eds.  1999.01

  • Toward the realization of an evolving ecosystem on cellular automata

    Proceedings of the Fourth International Symposium on Artificial Life and Robotics (AROB 4th '99), M. Sugisaka and H. Tanaka, eds.  1999.01

  • Spontaneous evolution of self-reproducing loops on cellular automata

    InterJournal (also published in Unifying Themes in Complex Systems Volume II: Proceedings of the Second International Conference on Complex Systems, Y. Bar-Yam and A. A. Minai, eds, 363-374, Westview Press, 2003)  1998.10

  • Spontaneous evolution of self-reproducing loops on cellular automata

    InterJournal (also published in Unifying Themes in Complex Systems Volume II: Proceedings of the Second International Conference on Complex Systems, Y. Bar-Yam and A. A. Minai, eds, 363-374, Westview Press, 2003)  1998.10

  • Langtonの自己増殖ループをもとに構成した構造解消可能型自己増殖ループの挙動に関する考察

    第12回人工知能学会全国大会論文集  1998.06

  • Introduction of structural dissolution into Langton's self-reproducing loop

    Artificial Life VI: Proceedings of the Sixth International Conference on Artificial Life, C. Adami, R. K. Belew, H. Kitano and C. E. Taylor, eds., MIT Press  1998.06

  • Introduction of structural dissolution into Langton's self-reproducing loop

    Artificial Life VI: Proceedings of the Sixth International Conference on Artificial Life, C. Adami, R. K. Belew, H. Kitano and C. E. Taylor, eds., MIT Press  1998.06

  • プログラムされた自己解体モデルによる進化システム

    第13回ファジィシステムシンポジウム講演論文集  1997.06

  • “プログラムされた自己解体モデル”検証のための高並列人工生命個体群シミュレータの開発

    並列処理シンポジウム(JSPP'97)論文集  1997.05

  • Artificial life based on programmed self-decomposition model

    Poster Proceedings of the Fifth International Workshop on the Synthesis and Simulation of Living Systems (ALIFE V), Nara, Japan  1996.05

  • Artificial life based on programmed self-decomposition model

    Poster Proceedings of the Fifth International Workshop on the Synthesis and Simulation of Living Systems (ALIFE V), Nara, Japan  1996.05

  • 高速大容量情報通信環境における高精細度動画像伝送評価用映像の開発

    1996年電子情報通信学会総合大会講演論文集  1996.03

  • SIVA: Artificial life based on programmed self-decomposition model

    Proceedings of the Fifth Parallel Computing Workshop (PCW'95 Japan)  1996.03

  • SIVA: Artificial life based on programmed self-decomposition model

    Proceedings of the Fifth Parallel Computing Workshop (PCW'95 Japan)  1996.03

  • Programed self-decomposition model and artificial life

    Proceedings of the 1995 International Workshop on Biologically Inspired Evolutionary Systems  1995.05

  • Programed self-decomposition model and artificial life

    Proceedings of the 1995 International Workshop on Biologically Inspired Evolutionary Systems  1995.05

  • 不規則場モデルによる超並列処理

    文部省重点領域研究「超並列原理に基づく情報処理基本体系」第6回シンポジウム予稿集  1995.03

  • プログラムされた自己解体モデルのコンピュータシミュレーション

    第23回数値解析シンポジウム予稿集  1994.06

  • 不規則場モデルによる超並列処理

    文部省重点領域研究「超並列原理に基づく情報処理基本体系」第5回シンポジウム予稿集  1994.02

▼display all

Research Projects

  • グラフ書換系を活用したテンポラルネットワークデータからの動的モデルの自動導出

    日本学術振興会  科学研究費助成事業 基盤研究(B)

    Project Year :

    2023.04
    -
    2027.03
     

    佐山 弘樹

  • 目標の共有は人々にワクチン接種の社会的ジレンマを乗り越えさせるか

    日本学術振興会  科学研究費助成事業 基盤研究(B)

    Project Year :

    2022.04
    -
    2026.03
     

    一ノ瀬 元喜, 佐山 弘樹, 伊東 啓

  • How does diversity of individuals affect the structure of society?: A constructive approach using adaptive networks

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research Grant-in-Aid for Scientific Research (B)

    Project Year :

    2019.04
    -
    2023.03
     

  • Spontaneous ideological escalation without leaders as a distributed socio-dynamical process

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research Grant-in-Aid for Challenging Research (Exploratory)

    Project Year :

    2019.06
    -
    2022.03
     

  • Integration of online experiments and agent-based model to dynamic social dilemma

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research Grant-in-Aid for Scientific Research (C)

    Project Year :

    2019.04
    -
    2022.03
     

    Ichinose Genki

     View Summary

    We obtained the following results of a dynamic social dilemma. First, we found that zero determinant strategies can exist even if a discount factor and/or observation errors are considered. Next, in the crowd evacuation dilemma, body turning behaviors were effective to shorten the evacuation time. Finally, in simulations where agents move by Levy flights and play the social dilemma game, we showed that moving with building good relationships with others can contribute to the realization of cooperative societies.

  • Effective vaccination strategies that prevent pandemic in multilayer networks

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research Grant-in-Aid for Young Scientists (B)

    Project Year :

    2017.04
    -
    2019.03
     

    Ichinose Genki, YOSHIMURA Jin, TAINAKA Kei-ichi, ITO Hiromu, SAYAMA Hiroki, SATOTANI Yoshiki

     View Summary

    We first investigated the effect of directional movements on the outspreading and prevention of disease in a one dimensional model. By extensive simulations, we found that when the density is lower than the critical limit, diseases finally become extinct because the interaction among individuals disappears in the meantime. In contrast, when the density is higher than the critical limit, diseases always exist due to continuous contacts among individuals.
    We second investigated how network structures affect the final epidemic sizes when individuals randomly moves among patches. The results showed that diseases never go extinct in the case of heterogeneous networks which have hubs because the hubs become the source of the diseases.

  • The Impact of Technological Relatedness on Firm Performance after Acquisitions

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research Grant-in-Aid for Challenging Exploratory Research

    Project Year :

    2016.04
    -
    2018.03
     

    YAMANOI JUNICHI, SAYAMA Hiroki, ASADA Yuki

     View Summary

    This study examines how technological relatedness between acquiring and acquired firms influences after-acquisition performance, measured based on financial and innovation outputs. Its sample is acquisitions implemented by Japanese listed firms from 1997 to 2006. Using patent data, reflecting longitudinal change in patent ownership, I measured inter-firm technological relatedness using network analysis. Preliminary results are that technological relatedness between acquiring and acquired firms has a curvilinear impact on the acquiring firm’s cumulative abnormal return and the number of registered patents after its acquisition.

  • 自己複製する万能製作機械の運動学的モデルの構築

    日本学術振興会  科学研究費助成事業 若手研究(B)

    Project Year :

    2005
     
     
     

    佐山 弘樹

  • マルチエージェントシステムが示す局所的・大域的挙動の理論的解析

  • 空間的分布を持ち局所的に交配する個体群における自発的パターン生成とその進化過程の研究

  • 自己複製し進化する人工システムの構築

  • Theoretical Analysis of Local and Global Behaviors of Multi-Agent Systems

  • Emergence and Evolution of Patterns in Spatially Distributed Locally Interacting Populations

  • Construction of Self-Replicating and Evolving Artificial Systems

▼display all

Misc

  • 適応的ネットワーク型人工社会モデルによる社会分断の考察

    佐山 弘樹

    人工知能   37 ( 1 ) 43 - 49  2022.01

    DOI CiNii

  • Visualizing Collective Idea Generation and Innovation Processes in Social Networks

    Yiding Cao, Yingjun Dong, Minjun Kim, Neil G. MacLaren, Sriniwas Pandey, Shelley D. Dionne, Francis J. Yammarino, Hiroki Sayama

    CoRR   abs/2110.09893  2021.10

     View Summary

    Collective idea generation and innovation processes are complex and dynamic,
    involving a large amount of qualitative narrative information that is difficult
    to monitor, analyze and visualize using traditional methods. In this study, we
    developed three new visualization methods for collective idea generation and
    innovation processes and applied them to data from online collaboration
    experiments. The first visualization is the Idea Cloud, which helps monitor
    collective idea posting activity and intuitively tracks idea clustering and
    transition. The second visualization is the Idea Geography, which helps
    understand how the idea space and its utility landscape are structured and how
    collaboration was performed in that space. The third visualization is the Idea
    Network, which connects idea dynamics with the social structure of the people
    who generated them, displaying how social influence among neighbors may have
    affected collaborative activities and where innovative ideas arose and spread
    in the social network.

    DOI

  • How Lévy flights triggered by presence of defectors affect evolution of cooperation in spatial games

    Genki Ichinose, Daiki Miyagawa, Erika Chiba, Hiroki Sayama

    Artificial Life   29 ( 2 ) 187 - 197  2021.05  [International journal]

     View Summary

    Cooperation among individuals has been key to sustaining societies. However,
    natural selection favors defection over cooperation. Cooperation can be favored
    when the mobility of individuals allows cooperators to form a cluster (or
    group). Mobility patterns of animals sometimes follow a L\'evy flight. A L\'evy
    flight is a kind of random walk but it is composed of many small movements with
    a few big movements. Here, we developed an agent-based model in a square
    lattice where agents perform L\'evy flights depending on the fraction of
    neighboring defectors. For comparison, we also tested normal-type movements
    implemented by a uniform distribution. We focus on how the sensitivity to
    defectors when performing L\'evy flights promotes the evolution of cooperation.
    Results of evolutionary simulations showed that L\'evy flights outperformed
    normal movements for cooperation in all sensitivities. In L\'evy flights,
    cooperation was most promoted when the sensitivity to defectors was moderate.
    Finally, as the population density became larger, higher sensitivity was more
    beneficial for cooperation to evolve.

    DOI PubMed

  • Utterance Clustering Using Stereo Audio Channels

    Yingjun Dong, Neil G. MacLaren, Yiding Cao, Francis J. Yammarino, Shelley D. Dionne, Michael D. Mumford, Shane Connelly, Hiroki Sayama, Gregory A. Ruark

    Computational intelligence and neuroscience   2021   6151651 - 6151651  2020.09  [International journal]

     View Summary

    Utterance clustering is one of the actively researched topics in audio signal
    processing and machine learning. This study aims to improve the performance of
    utterance clustering by processing multichannel (stereo) audio signals.
    Processed audio signals were generated by combining left- and right-channel
    audio signals in a few different ways and then extracted embedded features
    (also called d-vectors) from those processed audio signals. This study applied
    the Gaussian mixture model for supervised utterance clustering. In the training
    phase, a parameter sharing Gaussian mixture model was conducted to train the
    model for each speaker. In the testing phase, the speaker with the maximum
    likelihood was selected as the detected speaker. Results of experiments with
    real audio recordings of multi-person discussion sessions showed that the
    proposed method that used multichannel audio signals achieved significantly
    better performance than a conventional method with mono audio signals in more
    complicated conditions.

    DOI PubMed

  • Reduced mobility of infected agents suppresses but lengthens disease in biased random walk

    Genki Ichinose, Yoshiki Satotani, Hiroki Sayama, Takashi Nagatani

       2018.07

     View Summary

    Various theoretical models have been proposed to understand the basic nature
    of epidemics. Recent studies focus on the effects of mobility to epidemic
    process. However, uncorrelated random walk is typically assumed as the type of
    movement. In our daily life, the movement of people sometimes tends to be
    limited to a certain direction, which can be described by biased random walk.
    Here, we developed an agent-based model of susceptible-infected-recovered (SIR)
    epidemic process in a 2D continuous space where agents tend to move in a
    certain direction in addition to random movement. Moreover, we mainly focus on
    the effect of the reduced mobility of infected agents. Our model assumes that,
    when people are infected, their movement activity is greatly reduced because
    they are physically weakened by the disease. By conducting extensive
    simulations, we found that when the movement of infected people is limited, the
    final epidemic size becomes small. However, that crucially depended on the
    movement type of agents. Furthermore, the reduced mobility of infected agents
    lengthened the duration of the epidemic because the infection progressed
    slowly.

  • NiCE Teacher Workshop: Engaging K-12 Teachers in the Development of Curricular Materials That Utilize Complex Networks Concepts

    Emma K. Towlson, Lori Sheetz, Ralucca Gera, Jon Roginski, Catherine Cramer, Stephen Uzzo, Hiroki Sayama

    COMPLICITY-AN INTERNATIONAL JOURNAL OF COMPLEXITY AND EDUCATION   15 ( 1 ) 5 - 18  2018.05

    Other  

     View Summary

    Our educational systems must prepare students for an increasingly
    interconnected future, and teachers require equipping with modern tools, such
    as network science, to achieve this. We held a Networks in Classroom Education
    (NiCE) workshop for a group of 21 K-12 teachers with various disciplinary
    backgrounds. The explicit aim of this was to introduce them to concepts in
    network science, show them how these concepts can be utilized in the classroom,
    and empower them to develop resources, in the form of lesson plans, for
    themselves and the wider community. Here we detail the nature of the workshop
    and present its outcomes - including an innovative set of publicly available
    lesson plans. We discuss the future for successful integration of network
    science in K-12 education, and the importance of inspiring and enabling our
    teachers.

  • A Percolation-based Thresholding Method with Applications in Functional Connectivity Analysis

    Farnaz Zamani Esfahlani, Hiroki Sayama

       2017.10

     View Summary

    Despite the recent advances in developing more effective thresholding methods
    to convert weighted networks to unweighted counterparts, there are still
    several limitations that need to be addressed. One such limitation is the
    inability of the most existing thresholding methods to take into account the
    topological properties of the original weighted networks during the
    binarization process, which could ultimately result in unweighted networks that
    have drastically different topological properties than the original weighted
    networks. In this study, we propose a new thresholding method based on the
    percolation theory to address this limitation. The performance of the proposed
    method was validated and compared to the existing thresholding methods using
    simulated and real-world functional connectivity networks in the brain.
    Comparison of macroscopic and microscopic properties of the resulted unweighted
    networks to the original weighted networks suggest that the proposed
    thresholding method can successfully maintain the topological properties of the
    original weighted networks.

  • Diversity and Social Network Structure in Collective Decision Making: Evolutionary Perspectives with Agent-Based Simulations

    Shelley D. Dionne, Hiroki Sayama, Francis J. Yammarino

       2013.11

     View Summary

    Collective, especially group-based, managerial decision making is crucial in
    organizations. Using an evolutionary theoretic approach to collective decision
    making, agent-based simulations were conducted to investigate how human
    collective decision making would be affected by the agents' diversity in
    problem understanding and/or behavior in discussion, as well as by their social
    network structure. Simulation results indicated that groups with consistent
    problem understanding tended to produce higher utility values of ideas and
    displayed better decision convergence, but only if there was no group-level
    bias in collective problem understanding. Simulation results also indicated the
    importance of balance between selection-oriented (i.e., exploitative) and
    variation-oriented (i.e., explorative) behaviors in discussion to achieve
    quality final decisions. Expanding the group size and introducing non-trivial
    social network structure generally improved the quality of ideas at the cost of
    decision convergence. Simulations with different social network topologies
    revealed collective decision making on small-world networks with high local
    clustering tended to achieve highest decision quality more often than on random
    or scale-free networks. Implications of this evolutionary theory and simulation
    approach for future managerial research on collective, group, and multi-level
    decision making are discussed.

  • Visualizing Evolutionary Dynamics of Self-Replicators: A Graph-Based Approach.

    Chris Salzberg, Antony Antony, Hiroki Sayama

    Artif. Life   12 ( 3 ) 457 - 457  2006

    DOI

  • BisNet : An Information Sharing System Using Bookmarks of Web Browsers

    SANO Koji, SAYAMA Hiroki

    Transactions of the Japanese Society for Artificial Intelligence   20 ( 4 ) in press - 288  2005.03

     View Summary

    We propose a new information sharing system, named ``BisNet'', which automatically gathers information about the bookmarks stored in users' web browsers and helps the users exchange URIs of possibly interesting web pages with others who have similar interest with them. Being different from other typical agent services that gather and provide information according to pre-registered user profiles, BisNet is expected to share more relevant information because of its use of web browser bookmarks that are actively selected and ordered by many humans. To enhance the relevance of information being shared, we developed a novel algorithm for directory evaluation. This algorithm only looks at the local referential structure between bookmark directories and URIs and calculates for each directory the ``order index'' that represents how well its content URIs are put in order with a focus on specific areas of interest. Then each directory receives new URIs from other related directories with large order indexes. The repetition of such URI exchanges makes the whole directory-URI networks dynamically form directory groups according to the commonness of the URIs they refer to. Our method is unique in that it pays no attention to the actual contents of web pages, and thus is much simpler and faster than other methods based on the result of content analysis. We carried out a field trial that involved 45 people who used a prototype version of BisNet clients. The result indicated that the relevance of shared URIs positively correlated with the ``order index'' of surrounding related directories, demonstrating the effectiveness of the method we proposed.

    DOI CiNii

  • Autonomous URI sharing over networks of bookmark directories achieved by analyzing local network topologies

    ネットワーク生態学シンポジウム予稿集,情報処理学会ネットワーク生態学研究会     in press  2005.03

  • Autonomous URI sharing over networks of bookmark directories achieved by analyzing local network topologies

    Network Ecology Symposium, IPSJ SIG-Network Ecology     in press  2005.03

  • BisNet: An information sharing system using bookmarks of web browsers

    Koji Sano, Hiroki Sayama

    Transactions of the Japanese Society for Artificial Intelligence   20 ( 4 ) 281 - 288  2005

     View Summary

    We propose a new information sharing system, named "BisNet", which automatically gathers information about the bookmarks stored in users' web browsers and helps the users exchange URIs of possibly interesting web pages with others who have similar interest with them. Being different from other typical agent services that gather and provide information according to pre-registered user profiles, BisNet is expected to share more relevant information because of its use of web browser bookmarks that are actively selected and ordered by many humans. To enhance the relevance of information being shared, we developed a novel algorithm for directory evaluation. This algorithm only looks at the local referential structure between bookmark directories and URIs and calculates for each directory the "order index" that represents how well its content URIs are put in order with a focus on specific areas of interest. Then each directory receives new URIs from other related directories with large order indexes. The repetition of such URI exchanges makes the whole directory-URI networks dynamically form directory groups according to the commonness of the URIs they refer to. Our method is unique in that it pays no attention to the actual contents of web pages, and thus is much simpler and faster than other methods based on the result of content analysis. We carried out a field trial that involved 45 people who used a prototype version of BisNet clients. The result indicated that the relevance of shared URIs positively correlated with the "order index" of surrounding related directories, demonstrating the effectiveness of the method we proposed.

    DOI

  • Complex genetic evolution of artificial self-replicators in cellular automata

    Complexity   10 ( 2 ) 33 - 39  2004.12

    DOI

  • Evolutionary dynamics of cellular automata-based self-replicators in hostile environments

    C Salzberg, A Antony, H Sayama

    BIOSYSTEMS   78 ( 1-3 ) 119 - 134  2004.12

     View Summary

    In this paper we investigate population dynamics, genealogy and complexity-increase of locally interacting populations of cellular automata-based evolving self-replicating loops (evoloops). We outline experiments indicating that the evolutionary growth in complexity, known to be achievable in principle given the complete genetic accessibility granted by universal construction, may be achievable in practice using much simpler replicating structures. By introducing evoloop populations to hostile environments, we demonstrate that selection pressures toward smaller species can be mediated to enable evolutionary accessibility to larger species, which themselves roam a much more vast portion of genetic state-space. We show that this growth in size results from intrinsically biased genealogy inherent in the rules of the evoloop CA, normally suppressed by selection pressures from direct competition favouring the smallest species. This shows that, in populations of simple self-replicating structures, a limited form of complexity-increase may result from a process which is driven by biased genealogical connectivity-a purely emergent property arising out of bottom-up evolutionary dynamics-and not just by adaptation. Implications of this result are discussed and contrasted with other self-replication studies in Artificial Life and Biology. (C) 2004 Elsevier Ireland Ltd. All rights reserved.

    DOI

  • Evolutionary dynamics of cellular automata-based self-replicators in hostile environments

    C Salzberg, A Antony, H Sayama

    BIOSYSTEMS   78 ( 1-3 ) 119 - 134  2004.12

     View Summary

    In this paper we investigate population dynamics, genealogy and complexity-increase of locally interacting populations of cellular automata-based evolving self-replicating loops (evoloops). We outline experiments indicating that the evolutionary growth in complexity, known to be achievable in principle given the complete genetic accessibility granted by universal construction, may be achievable in practice using much simpler replicating structures. By introducing evoloop populations to hostile environments, we demonstrate that selection pressures toward smaller species can be mediated to enable evolutionary accessibility to larger species, which themselves roam a much more vast portion of genetic state-space. We show that this growth in size results from intrinsically biased genealogy inherent in the rules of the evoloop CA, normally suppressed by selection pressures from direct competition favouring the smallest species. This shows that, in populations of simple self-replicating structures, a limited form of complexity-increase may result from a process which is driven by biased genealogical connectivity-a purely emergent property arising out of bottom-up evolutionary dynamics-and not just by adaptation. Implications of this result are discussed and contrasted with other self-replication studies in Artificial Life and Biology. (C) 2004 Elsevier Ireland Ltd. All rights reserved.

    DOI

  • Complex genetic evolution of artificial self-replicators in cellular automata

    C Salzberg, H Sayama

    COMPLEXITY   10 ( 2 ) 33 - 39  2004.11

     View Summary

    It is widely believed that evolutionary dynamics of artificial self-replicators realized in cellular automata (CA) are limited in diversity and adaptation. Contrary to this view, we show that complex genetic evolution may occur within simple CA. The evolving self-replicating loops ("evoloops") we investigate exhibit significant diversity in macro-scale morphologies and mutational biases, undergoing nontrivial genetic adaptation by maximizing colony density and enhancing sustainability against other species. Nonmutable subsequences enable genetic operations that alter fitness differentials and promote long-term evolutionary exploration. These results demonstrate a unique example of genetic evolution hierarchically emerging from local interactions between elements much smaller than individual replicators. (c) 2004 Wiley Periodicals, Inc.

    DOI

  • セルオートマトン上における自己複製ループの複雑な遺伝的進化

    日本進化学会第6回大会講演要旨集     26 / 119  2004.08

  • Complex genetic evolution of self-replicating loops in cellular automata

    Proceedings of the Sixth Annual Meeting of the Society of Evolutionary Studies, Japan     26 / 119  2004.08

  • Self-protection and diversity in self-replicating cellular automata

    Fifth International Conference on Complex Systems (ICCS2004), abstract available at http://necsi.net/events/iccs/openconf/author/abstractbook.php    2004.05

    DOI

  • Self-protection and diversity in self-replicating cellular automata

    Fifth International Conference on Complex Systems (ICCS2004), abstract available at http://necsi.net/events/iccs/openconf/author/abstractbook.php    2004.05

    DOI

  • Self-protection and diversity in self-replicating cellular automata

    Artificial Life   10 ( 1 ) 83 - 98  2004.03

    DOI

  • Self-protection and diversity in self-replicating cellular automata

    Artificial Life   10 ( 1 ) 83 - 98  2004.03

    DOI

  • Living Surfaces A Concept of Animated Texture using "Evoloop" and Experiments in an Interactive Art:A Concept of Animated Texture using "Evoloop" and Experiments in an Interactive Art

    KODAMA Sachiko, FUKUDA Yoko, SAYAMA Hiroki, KOIKE Hideki

    The Journal of the Society for Art and Science   3 ( 3 ) 193 - 196  2004

     View Summary

    In this paper we describe a concept of animated texture using A-life model called "evoloop." The texture transforms interactively according to the input by image recognition. We created an interactive art <living surfaces> using this technique. <Living Surfaces> is an interactive art realizing dynamic transformations of animated textures. On the square canvas, a complicated computer-generated color abstract image is projected, dynamically changing when people move their bodies or small black geometric shapes on it. The evolving patterns generated by "evoloop" appear according to the position of the black shapes. On the rectangle canvas, a three-dimensional creature image is projected, the texture of which reflects the pattern generated on the square canvas.

    DOI CiNii

  • A tangled hierarchy of graph-constructing graphs

    C Salzberg, H Sayama, T Ikegami

    Artificial Life IX     495 - 500  2004

     View Summary

    The traditional construction paradigm of machine and tape is reformulated in a functionally homogeneous space of directed graph structures. Hierarchy-based roles, normally appointed to actors in a construction process, are dissolved and replaced by symmetric, level-less engagement. The separation between static (information carrying) and active (information processing) structures, imposed by mandate of the rules or physics in earlier theoretical models, results instead purely from graph topology. While encompassing traditional machine-tape paradigms as a special case, the formalism is shown to incorporate a wider class of construction relations. Exploiting its flexibility, a representation of a Turing machine is demonstrated, establishing computation universality. The concept of a "Tangled Construction Hierarchy" is introduced.

  • Living Surfaces A Concept of Animated Texture using "Evoloop" and Experiments in an Interactive Art:A Concept of Animated Texture using "Evoloop" and Experiments in an Interactive Art

    KODAMA Sachiko, FUKUDA Yoko, SAYAMA Hiroki, KOIKE Hideki

    The Journal of the Society for Art and Science   3 ( 3 ) 193 - 196  2004

     View Summary

    In this paper we describe a concept of animated texture using A-life model called "evoloop." The texture transforms interactively according to the input by image recognition. We created an interactive art <living surfaces> using this technique. <Living Surfaces> is an interactive art realizing dynamic transformations of animated textures. On the square canvas, a complicated computer-generated color abstract image is projected, dynamically changing when people move their bodies or small black geometric shapes on it. The evolving patterns generated by "evoloop" appear according to the position of the black shapes. On the rectangle canvas, a three-dimensional creature image is projected, the texture of which reflects the pattern generated on the square canvas.

    DOI CiNii

  • A tangled hierarchy of graph-constructing graphs

    C Salzberg, H Sayama, T Ikegami

    Artificial Life IX     495 - 500  2004

     View Summary

    The traditional construction paradigm of machine and tape is reformulated in a functionally homogeneous space of directed graph structures. Hierarchy-based roles, normally appointed to actors in a construction process, are dissolved and replaced by symmetric, level-less engagement. The separation between static (information carrying) and active (information processing) structures, imposed by mandate of the rules or physics in earlier theoretical models, results instead purely from graph topology. While encompassing traditional machine-tape paradigms as a special case, the formalism is shown to incorporate a wider class of construction relations. Exploiting its flexibility, a representation of a Turing machine is demonstrated, establishing computation universality. The concept of a "Tangled Construction Hierarchy" is introduced.

  • Visualizing evolutionary dynamics of self-replicators: A graph-based approach

    Artificial Life     in press  2004

  • Genetic diversification and complex genealogy of self-replicators discovered in simple cellular automata: A preliminary report

    3次元映像のフォーラム会誌「3D映像」   17 ( 4 ) 103 - 109  2003.12

  • Genetic diversification and complex genealogy of self-replicators discovered in simple cellular automata: A preliminary report

    Journal of Three Dimensional Images, 3D Forum, Japan   17 ( 4 ) 103 - 109  2003.12

  • Protocols for negotiating complex contracts

    M Klein, P Faratin, H Sayama, Y Bar-Yam

    IEEE INTELLIGENT SYSTEMS   18 ( 6 ) 32 - 38  2003.11

    DOI

  • Protocols for negotiating complex contracts

    M Klein, P Faratin, H Sayama, Y Bar-Yam

    IEEE INTELLIGENT SYSTEMS   18 ( 6 ) 32 - 38  2003.11

    DOI

  • Robustness of spontaneous pattern formation in spatially distributed genetic populations

    MAM de Aguiar, M Baranger, Y Bar-Yam, H Sayama

    BRAZILIAN JOURNAL OF PHYSICS   33 ( 3 ) 514 - 520  2003.09

     View Summary

    Spatially distributed genetic populations that compete locally for resources and mate only with sufficiently close neighbors, may give rise to spontaneous pattern formation. Depending on the population parameters, like death rate per generation and size of the competition and mating neighborhoods, isolated groups of individuals, or demes, may appear. The existence of such groups in a population has consequences for genetic diversity and for speciation. In this paper we discuss the robustness of demes formation with respect to two important characteristics of the population: the way individuals recognize the demarcation of the local neighborhoods and the way competition for resources affects the birth rate in an overcrowed situation. Our results indicate that demes are expected to form only for sufficiently sharp demarcations and for sufficiently intense competition.

  • The dynamics of collaborative design: Insights from complex systems and negotiation research

    M Klein, H Sayama, P Faratin, Y Bar-Yam

    CONCURRENT ENGINEERING-RESEARCH AND APPLICATIONS   11 ( 3 ) 201 - 209  2003.09

     View Summary

    Almost all complex artifacts nowadays, including physical artifacts such as airplanes, as well as informational artifacts such as software, organizations, business processes, plans, and schedules, are defined via the interaction of many, sometimes thousands of participants, working on different elements of the design. This collaborative design process is typically expensive and time-consuming because strong interdependencies between design decisions make it difficult to converge on a single design that satisfies these dependencies and is acceptable to all participants. Recent research from the complex systems and negotiation literatures has much to offer to the understanding of the dynamics of this process. This paper reviews some of these insights and offers suggestions for improving collaborative design.

    DOI

  • Robustness of spontaneous pattern formation in spatially distributed genetic populations

    MAM de Aguiar, M Baranger, Y Bar-Yam, H Sayama

    BRAZILIAN JOURNAL OF PHYSICS   33 ( 3 ) 514 - 520  2003.09

     View Summary

    Spatially distributed genetic populations that compete locally for resources and mate only with sufficiently close neighbors, may give rise to spontaneous pattern formation. Depending on the population parameters, like death rate per generation and size of the competition and mating neighborhoods, isolated groups of individuals, or demes, may appear. The existence of such groups in a population has consequences for genetic diversity and for speciation. In this paper we discuss the robustness of demes formation with respect to two important characteristics of the population: the way individuals recognize the demarcation of the local neighborhoods and the way competition for resources affects the birth rate in an overcrowed situation. Our results indicate that demes are expected to form only for sufficiently sharp demarcations and for sufficiently intense competition.

  • The dynamics of collaborative design: Insights from complex systems and negotiation research

    M Klein, H Sayama, P Faratin, Y Bar-Yam

    CONCURRENT ENGINEERING-RESEARCH AND APPLICATIONS   11 ( 3 ) 201 - 209  2003.09

     View Summary

    Almost all complex artifacts nowadays, including physical artifacts such as airplanes, as well as informational artifacts such as software, organizations, business processes, plans, and schedules, are defined via the interaction of many, sometimes thousands of participants, working on different elements of the design. This collaborative design process is typically expensive and time-consuming because strong interdependencies between design decisions make it difficult to converge on a single design that satisfies these dependencies and is acceptable to all participants. Recent research from the complex systems and negotiation literatures has much to offer to the understanding of the dynamics of this process. This paper reviews some of these insights and offers suggestions for improving collaborative design.

    DOI

  • 物理世界において自己複製するおもちゃの実現にむけたシミュレーションモデルの提案

    第9回創発システム・シンポジウム「創発夏の学校2003」講演資料,計測自動制御学会システム・情報部門     94 - 97  2003.08

  • A simulation model of toys that self-replicate in a physical world

    Proceedings of the 9th Emergent Systems Symposium (Summer School on Emergence 2003), SICE     94 - 97  2003.08

  • Interplay between Turing Pattern Formation and Domain Coarsening in Spatially Extended Population Models

    SAYAMA Hiroki, DE AGUIAR Marcus A. M., BAR-YAM Yaneer, BARANGER Michel

      18 ( 1 ) 19 - 36  2003.06

    CiNii

  • Spontaneous pattern formation and genetic diversity in habitats with irregular geographical features

    H Sayama, L Kaufman, Y Bar-Yam

    CONSERVATION BIOLOGY   17 ( 3 ) 893 - 900  2003.06

     View Summary

    The role of spontaneous pattern formation, the appearance of inhomogeneities that are not directly imposed by external forces, has not been closely examined in the context of the origin and maintenance of genetic diversity in wild populations. Using individual-based computer simulations, we demonstrated that such patterns form in spatially distributed species with local demes under disruptive selection. In our model systems, spatial patterns of genetic diversity arose and changed over time even in the context of a spatially homogenous environment. The spatial distribution and dynamics of the fittest genotypes were controlled by the movement of boundaries between domains of the different genotypes. The rate of diversity decay was dramatically slower than predicted by traditional models. Therefore, spontaneous pattern formation may lead to the maintenance of genetic diversity of a species in a contiguous habitat, despite reproductive mixing. Moreover, the diversity persisted significantly longer in larger habitats and habitats with irregular geographical features. Habitat structure was intimately linked to the preservation of genetic diversity. Spontaneous pattern formation should be considered along with other spatial effects in the design of conservation areas.

    DOI

  • Interplay between Turing pattern formation and domain coarsening in spatially extended population models

    SAYAMA Hiroki, DE AGUIAR Marcus A. M., BAR-YAM Yaneer, BARANGER Michel

    FORMA   18 ( 1 ) 19 - 36  2003.06

    CiNii

  • Spontaneous pattern formation and genetic diversity in habitats with irregular geographical features

    H Sayama, L Kaufman, Y Bar-Yam

    CONSERVATION BIOLOGY   17 ( 3 ) 893 - 900  2003.06

     View Summary

    The role of spontaneous pattern formation, the appearance of inhomogeneities that are not directly imposed by external forces, has not been closely examined in the context of the origin and maintenance of genetic diversity in wild populations. Using individual-based computer simulations, we demonstrated that such patterns form in spatially distributed species with local demes under disruptive selection. In our model systems, spatial patterns of genetic diversity arose and changed over time even in the context of a spatially homogenous environment. The spatial distribution and dynamics of the fittest genotypes were controlled by the movement of boundaries between domains of the different genotypes. The rate of diversity decay was dramatically slower than predicted by traditional models. Therefore, spontaneous pattern formation may lead to the maintenance of genetic diversity of a species in a contiguous habitat, despite reproductive mixing. Moreover, the diversity persisted significantly longer in larger habitats and habitats with irregular geographical features. Habitat structure was intimately linked to the preservation of genetic diversity. Spontaneous pattern formation should be considered along with other spatial effects in the design of conservation areas.

    DOI

  • Dynamics and genealogy of strains in spatially extended host-pathogen models.

    Erik M Rauch, Hiroki Sayama, Yaneer Bar-Yam

    Journal of theoretical biology   221 ( 4 ) 655 - 64  2003.04  [International journal]

     View Summary

    We examine the dynamics of evolution in a generic spatial model of a pathogen infecting a population of hosts, or an analogous predator-prey system. Previous studies of this model have found a range of interesting phenomena that differ from the well-mixed version. We extend these studies by examining the spatial and temporal dynamics of strains using genealogical tracing. When transmissibility can evolve by mutation, strains of intermediate transmissibility dominate even though high-transmissibility mutants have a short-term reproductive advantage. Mutant strains continually arise and grow rapidly for many generations but eventually go extinct before dominating the system. We find that, after a number of generations, the mutant pathogen characteristics strongly impact the spatial distribution of their local host environment, even when there are diverse types coexisting. Extinction is due to the depletion of susceptibles in the local environment of these mutant strains. Studies of spatial and genealogical relatedness reveal the self-organized spatial clustering of strains that enables their impact on the local environment. Thus, we find that selection acts against the high-transmissibility strains on long time-scales as a result of the feedback due to environmental change. Our study shows that averages over space or time should not be assumed to adequately describe the evolutionary dynamics of spatially distributed host-pathogen systems.

    DOI PubMed

  • Dynamics and genealogy of strains in spatially extended host-pathogen models

    EM Rauch, H Sayama, Y Bar-Yam

    JOURNAL OF THEORETICAL BIOLOGY   221 ( 4 ) 655 - 664  2003.04

     View Summary

    We examine the dynamics of evolution in a generic spatial model of a pathogen infecting a population of hosts, or an analogous predator-prey system. Previous studies of this model have found a range of interesting phenomena that differ from the well-mixed version. We extend these studies by examining the spatial and temporal dynamics of strains using genealogical tracing. When transmissibility can evolve by mutation, strains of intermediate transmissibility dominate even though high-transmissibility mutants have a short-term reproductive advantage. Mutant strains continually arise and grow rapidly for many generations but eventually go extinct before dominating the system. We find that, after a number of generations, the mutant pathogen characteristics strongly impact the spatial distribution of their local host environment, even when there are diverse types coexisting. Extinction is due to the depletion of susceptibles in the local environment of these mutant strains. Studies of spatial and genealogical relatedness reveal the self-organized spatial clustering of strains that enables their impact on the local environment. Thus, we find that selection acts against the high-transmissibility strains on long time-scales as a result of the feedback due to environmental change. Our study shows that averages over space or time should not be assumed to adequately describe the evolutionary dynamics of spatially distributed host-pathogen systems. (C) 2003 Elsevier Science Ltd. All rights reserved.

    DOI

  • Exploring diversity in emergent evolutionary systems using graph-based genealogy

    NVTB (Dutch Society for Theoretical Biology) Meeting 2003, Schoorl, The Netherlands, abstract available at http://www.bio.vu.nl/nvtb/Abstracts03.html    2003.03

  • Negotiating complex contracts

    M Klein, P Faratin, H Sayama, Y Bar-Yam

    GROUP DECISION AND NEGOTIATION   12 ( 2 ) 111 - 125  2003.03

     View Summary

    Work to date on computational models of negotiation has focused almost exclusively on defining contracts consisting of one or a few independent issues and tractable contract spaces. Many real-world contracts, by contrast, are much more complex, consisting of multiple inter-dependent issues and intractably large contract spaces. This paper describes a simulated annealing based approach appropriate for negotiating such complex contracts that achieves near-optimal social welfares for negotiations with binary issue dependencies.

    DOI

  • Exploring diversity in emergent evolutionary systems using graph-based genealogy

    NVTB (Dutch Society for Theoretical Biology) Meeting 2003, Schoorl, The Netherlands, abstract available at http://www.bio.vu.nl/nvtb/Abstracts03.html    2003.03

  • Negotiating complex contracts

    M Klein, P Faratin, H Sayama, Y Bar-Yam

    GROUP DECISION AND NEGOTIATION   12 ( 2 ) 111 - 125  2003.03

     View Summary

    Work to date on computational models of negotiation has focused almost exclusively on defining contracts consisting of one or a few independent issues and tractable contract spaces. Many real-world contracts, by contrast, are much more complex, consisting of multiple inter-dependent issues and intractably large contract spaces. This paper describes a simulated annealing based approach appropriate for negotiating such complex contracts that achieves near-optimal social welfares for negotiations with binary issue dependencies.

    DOI

  • Optimization of robustness and connectivity in complex networks.

    Benjamin Shargel, Hiroki Sayama, Irving R Epstein, Yaneer Bar-Yam

    Physical review letters   90 ( 6 ) 068701 - 068701  2003.02  [International journal]

     View Summary

    Scale-free networks rely on a relatively small number of highly connected nodes to achieve a high degree of interconnectivity and robustness to random failure, but suffer from a high sensitivity to directed attack. In this paper we describe a parameterized family of networks and analyze their connectivity and sensitivity, identifying a network that has an interconnectedness closer to that of a scale-free network, a robustness to attack closer to that of an exponential network, and a resistance to failure better than that of either of those networks.

    DOI PubMed

  • Optimization of robustness and connectivity in complex networks

    B Shargel, H Sayama, IR Epstein, Y Bar-Yam

    PHYSICAL REVIEW LETTERS   90 ( 6 ) 068701  2003.02

     View Summary

    Scale-free networks rely on a relatively small number of highly connected nodes to achieve a high degree of interconnectivity and robustness to random failure, but suffer from a high sensitivity to directed attack. In this paper we describe a parametrized family of networks and analyze their connectivity and sensitivity, identifying a network that has an interconnectedness closer to that of a scale-free network, a robustness to attack closer to that of an exponential network, and a resistance to failure better than that of either of those networks.

    DOI

  • Toward the physical implementation of artificial self-replicating and evolving systems

    Bulletin of the University of Electro-Communications, special issue, Tokyo, Japan (reselected from the Proceedings of IWMST-2002)   15-2   38 - 42  2003.01

  • Artificial Life(My Bookmark)

    ARITA Takaya, SAYAMA Hiroki, Takaya Arita, Hiroki Sayama

    Journal of the Japanese Society for Artificial Intelligence   18 ( 1 ) 90 - 93  2003.01

    DOI CiNii

  • Toward the physical implementation of artificial self-replicating and evolving systems

    Bulletin of the University of Electro-Communications, special issue, Tokyo, Japan (reselected from the Proceedings of IWMST-2002)   15-2   38 - 42  2003.01

  • A complex systems perspective on computer-supported collaborative design technology

    M Klein, H Sayama, P Faratin, Y Bar-Yam

    COMMUNICATIONS OF THE ACM   45 ( 11 ) 27 - 31  2002.11

  • Spontaneous pattern formation and genetic invasion in locally mating and competing populations

    International Conference on Morphogenesis and Pattern Formation in Biological Systems--Experiments and Models--(MPB2002), Chubu University, Nagoya, Japan     102  2002.09

  • Relationship between measures of fitness and time scale in evolution

    EM Rauch, H Sayama, Y Bar-Yam

    PHYSICAL REVIEW LETTERS   88 ( 22 ) 228101  2002.06

     View Summary

    The notion of fitness is central in evolutionary biology. We use a simple spatially extended predator-prey or host-pathogen model to show a generic case where the average number of offspring of an individual as a measure of fitness fails to characterize the evolutionary dynamics. Mutants with high initial reproduction ratios have lineages that eventually go extinct due to local overexploitation. We propose general quantitative measures of fitness that reflect the importance of time scale in evolutionary processes.

    DOI

  • Relationship between measures of fitness and time scale in evolution

    EM Rauch, H Sayama, Y Bar-Yam

    PHYSICAL REVIEW LETTERS   88 ( 22 ) 228101  2002.06

     View Summary

    The notion of fitness is central in evolutionary biology. We use a simple spatially extended predator-prey or host-pathogen model to show a generic case where the average number of offspring of an individual as a measure of fitness fails to characterize the evolutionary dynamics. Mutants with high initial reproduction ratios have lineages that eventually go extinct due to local overexploitation. We propose general quantitative measures of fitness that reflect the importance of time scale in evolutionary processes.

    DOI

  • Stability of polymorphic populations and genetic invasion by migration

    XXV ENFMC (the 25th Brazilian National Conference on Condensed Matter Physics), Caxambu, Brazil, abstract available at http://www.sbf1.if.usp.br/eventos/enfmc/xxv/programa/bio0056.htm     P041  2002.05

  • Spontaneous pattern formation and genetic invasion in locally mating and competing populations

    H Sayama, MAM de Aguiar, Y Bar-Yam, M Baranger

    PHYSICAL REVIEW E   65 ( 5 ) 051919  2002.05

     View Summary

    We present a theoretical model of evolution of spatially distributed populations in which organisms mate with and compete against each other only locally. We show using both analysis and numerical simulation that the typical dynamics of population density variation is a spontaneous formation of isolated groups due to competition for resources. The resulting spatial separation between groups strongly affects the process of genetic invasion by local reproductive mixing, and spatially inhomogeneous genetic distributions are possible in the final states. We then consider a specific version of this model in the presence of disruptive selection, favoring two fittest types against their genetic intermediates. This case can be simplified to a system that involves just two nonconserved order parameters: population density and type difference. Since the coexistence of two fittest types is unstable in this case, symmetry breaking and coarsening occur in type difference, implying eventual dominance by one type over another for finite populations. However, such coarsening patterns may be pinned by the spontaneously generated spatial separation between isolated groups. The long-term evolution of genetic composition is found to be sensitive to the ratio of the mating and competition ranges, and other parameters. Our model may provide a theoretical basis for consideration of various properties of spatially extended evolutionary processes, including spontaneous formation of subpopulations and lateral invasion of different types.

    DOI

  • Stability of polymorphic populations and genetic invasion by migration

    XXV ENFMC (the 25th Brazilian National Conference on Condensed Matter Physics), Caxambu, Brazil, abstract available at http://www.sbf1.if.usp.br/eventos/enfmc/xxv/programa/bio0056.htm     P041  2002.05

  • Spontaneous pattern formation and genetic invasion in locally mating and competing populations

    H Sayama, MAM de Aguiar, Y Bar-Yam, M Baranger

    PHYSICAL REVIEW E   65 ( 5 )  2002.05

     View Summary

    We present a theoretical model of evolution of spatially distributed populations in which organisms mate with and compete against each other only locally. We show using both analysis and numerical simulation that the typical dynamics of population density variation is a spontaneous formation of isolated groups due to competition for resources. The resulting spatial separation between groups strongly affects the process of genetic invasion by local reproductive mixing, and spatially inhomogeneous genetic distributions are possible in the final states. We then consider a specific version of this model in the presence of disruptive selection, favoring two fittest types against their genetic intermediates. This case can be simplified to a system that involves just two nonconserved order parameters: population density and type difference. Since the coexistence of two fittest types is unstable in this case, symmetry breaking and coarsening occur in type difference, implying eventual dominance by one type over another for finite populations. However, such coarsening patterns may be pinned by the spontaneously generated spatial separation between isolated groups. The long-term evolution of genetic composition is found to be sensitive to the ratio of the mating and competition ranges, and other parameters. Our model may provide a theoretical basis for consideration of various properties of spatially extended evolutionary processes, including spontaneous formation of subpopulations and lateral invasion of different types.

    DOI

  • Spontaneous pattern formation and genetic invasion in locally mating and competing populations.

    Hiroki Sayama, Marcus A M de Aguiar, Yaneer Bar-Yam, Michel Baranger

    Physical review. E, Statistical, nonlinear, and soft matter physics   65 ( 5 Pt 1 ) 051919 - 051919  2002.05  [International journal]

     View Summary

    We present a theoretical model of evolution of spatially distributed populations in which organisms mate with and compete against each other only locally. We show using both analysis and numerical simulation that the typical dynamics of population density variation is a spontaneous formation of isolated groups due to competition for resources. The resulting spatial separation between groups strongly affects the process of genetic invasion by local reproductive mixing, and spatially inhomogeneous genetic distributions are possible in the final states. We then consider a specific version of this model in the presence of disruptive selection, favoring two fittest types against their genetic intermediates. This case can be simplified to a system that involves just two nonconserved order parameters: population density and type difference. Since the coexistence of two fittest types is unstable in this case, symmetry breaking and coarsening occur in type difference, implying eventual dominance by one type over another for finite populations. However, such coarsening patterns may be pinned by the spontaneously generated spatial separation between isolated groups. The long-term evolution of genetic composition is found to be sensitive to the ratio of the mating and competition ranges, and other parameters. Our model may provide a theoretical basis for consideration of various properties of spatially extended evolutionary processes, including spontaneous formation of subpopulations and lateral invasion of different types.

    DOI PubMed

  • Stability and instability of polymorphic populations and the role of multiple breeding seasons in phase III of Wright&apos;s shifting balance theory

    MAM de Aguiar, H Sayama, E Rauch, Y Bar-Yam, M Baranger

    PHYSICAL REVIEW E   65 ( 3 ) 031909  2002.03

     View Summary

    It is generally difficult for a large population at a fitness peak to acquire the genotypes of a higher peak, because the intermediates produced by allelic recombination between types at different peaks are of lower fitness. In his shifting-balance theory, Wright proposed that fitter genotypes could, however, become fixed in small isolated demes by means of random genetic fluctuations. These demes would then try to spread their genome to nearby demes by migration of their individuals. The resulting polymorphism, the coexistence of individuals with different genotypes, would give the invaded demes a chance to move up to a higher fitness peak. This last step of the process, namely, the invasion of lower fitness demes by higher fitness genotypes, is known as phase III of Wright&apos;s theory. Here we study the invasion process from the point of view of the stability of polymorphic populations. Invasion occurs when the polymorphic equilibrium, established at low migration rates, becomes unstable. We show that the instability threshold depends sensitively on the average number of breeding seasons of individuals. Iteroparous species (with many breeding seasons! have lower thresholds than semelparous species (with a single breeding season). By studying a particular simple model, we are able to provide analytical estimates of the migration threshold as a function of the number of breeding seasons. Once the threshold is crossed and polymorphism becomes unstable, any imbalance between the different demes is sufficient for invasion to occur. The outcome of the invasion, however, depends on many parameters, not only on fitness. Differences in fitness, site capacities, relative migration rates, and initial conditions, all contribute to determine which genotype invades successfully. Contrary to the original perspective of Wright&apos;s theory for continuous fitness improvement, our results show that both upgrading to higher fitness peaks and downgrading to lower peaks are possible.

    DOI

  • Stability and instability of polymorphic populations and the role of multiple breeding seasons in phase III of Wright&apos;s shifting balance theory

    MAM de Aguiar, H Sayama, E Rauch, Y Bar-Yam, M Baranger

    PHYSICAL REVIEW E   65 ( 3 ) 031909  2002.03

     View Summary

    It is generally difficult for a large population at a fitness peak to acquire the genotypes of a higher peak, because the intermediates produced by allelic recombination between types at different peaks are of lower fitness. In his shifting-balance theory, Wright proposed that fitter genotypes could, however, become fixed in small isolated demes by means of random genetic fluctuations. These demes would then try to spread their genome to nearby demes by migration of their individuals. The resulting polymorphism, the coexistence of individuals with different genotypes, would give the invaded demes a chance to move up to a higher fitness peak. This last step of the process, namely, the invasion of lower fitness demes by higher fitness genotypes, is known as phase III of Wright&apos;s theory. Here we study the invasion process from the point of view of the stability of polymorphic populations. Invasion occurs when the polymorphic equilibrium, established at low migration rates, becomes unstable. We show that the instability threshold depends sensitively on the average number of breeding seasons of individuals. Iteroparous species (with many breeding seasons! have lower thresholds than semelparous species (with a single breeding season). By studying a particular simple model, we are able to provide analytical estimates of the migration threshold as a function of the number of breeding seasons. Once the threshold is crossed and polymorphism becomes unstable, any imbalance between the different demes is sufficient for invasion to occur. The outcome of the invasion, however, depends on many parameters, not only on fitness. Differences in fitness, site capacities, relative migration rates, and initial conditions, all contribute to determine which genotype invades successfully. Contrary to the original perspective of Wright&apos;s theory for continuous fitness improvement, our results show that both upgrading to higher fitness peaks and downgrading to lower peaks are possible.

    DOI

  • Spontaneous pattern formation and genetic invasion in locally mating and competing populations

    Hiroki Sayama, Marcus A. M. de Aguiar, Yaneer Bar-Yam, Michel Baranger

    Physical Review E - Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics   65 ( 5 ) 15  2002

     View Summary

    We present a theoretical model of evolution of spatially distributed populations in which organisms mate with and compete against each other only locally. We show using both analysis and numerical simulation that the typical dynamics of population density variation is a spontaneous formation of isolated groups due to competition for resources. The resulting spatial separation between groups strongly affects the process of genetic invasion by local reproductive mixing, and spatially inhomogeneous genetic distributions are possible in the final states. We then consider a specific version of this model in the presence of disruptive selection, favoring two fittest types against their genetic intermediates. This case can be simplified to a system that involves just two nonconserved order parameters: population density and type difference. Since the coexistence of two fittest types is unstable in this case, symmetry breaking and coarsening occur in type difference, implying eventual dominance by one type over another for finite populations. However, such coarsening patterns may be pinned by the spontaneously generated spatial separation between isolated groups. The long-term evolution of genetic composition is found to be sensitive to the ratio of the mating and competition ranges, and other parameters. Our model may provide a theoretical basis for consideration of various properties of spatially extended evolutionary processes, including spontaneous formation of subpopulations and lateral invasion of different types. © 2002 The American Physical Society.

    DOI

  • Spontaneous pattern formation and genetic invasion in locally mating and competing populations

    Hiroki Sayama, Marcus A. M. de Aguiar, Yaneer Bar-Yam, Michel Baranger

    Physical Review E - Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics   65 ( 5 ) 15  2002

     View Summary

    We present a theoretical model of evolution of spatially distributed populations in which organisms mate with and compete against each other only locally. We show using both analysis and numerical simulation that the typical dynamics of population density variation is a spontaneous formation of isolated groups due to competition for resources. The resulting spatial separation between groups strongly affects the process of genetic invasion by local reproductive mixing, and spatially inhomogeneous genetic distributions are possible in the final states. We then consider a specific version of this model in the presence of disruptive selection, favoring two fittest types against their genetic intermediates. This case can be simplified to a system that involves just two nonconserved order parameters: population density and type difference. Since the coexistence of two fittest types is unstable in this case, symmetry breaking and coarsening occur in type difference, implying eventual dominance by one type over another for finite populations. However, such coarsening patterns may be pinned by the spontaneously generated spatial separation between isolated groups. The long-term evolution of genetic composition is found to be sensitive to the ratio of the mating and competition ranges, and other parameters. Our model may provide a theoretical basis for consideration of various properties of spatially extended evolutionary processes, including spontaneous formation of subpopulations and lateral invasion of different types. © 2002 The American Physical Society.

    DOI

  • A complex systems perspective on computer-supported collaborative design technology.

    Mark Klein, Hiroki Sayama, Peyman Faratin, Yaneer Bar-Yam

    Commun. ACM   45 ( 11 ) 27 - 31  2002

    DOI

  • Interplay of genetic and actual lifespans

    H Sayama, Y Bar-Yam

    PHYSICAL REVIEW LETTERS   86 ( 20 ) 4718 - 4718  2001.05

    DOI PubMed

  • Symmetry breaking and coarsening in spatially distributed evolutionary processes including sexual reproduction and disruptive selection

    SAYAMA H, KAUFMAN L, BAR‐YAM Y

    Phys. Rev. E   62 ( 5,Pt.B ) 7065 - 7069  2000.11

    DOI PubMed CiNii

  • Symmetry breaking and coarsening in spatially distributed evolutionary processes including sexual reproduction and disruptive selection

    Phys. Rev. E   62 ( 5,Pt.B ) 7065 - 7069  2000.11

    DOI PubMed CiNii

  • A new structurally dissolvable self-reproducing loop evolving in a simple cellular automata space

    SAYAMA H

    Artificial Life   5 ( 4 ) 343 - 365  1999.12

    DOI PubMed CiNii

  • A new structurally dissolvable self-reproducing loop evolving in a simple cellular automata space

    Artificial Life   5 ( 4 ) 343 - 365  1999.12

    DOI PubMed CiNii

  • 書評「人工生命」(有田隆也著,科学技術出版)

    情報処理(情報処理学会学会誌)   40 ( 11 ) 1157 - 1158  1999.11

  • セルラオートマトンを用いた自己複製モデルについて

    第3回ALIST: ALIREN+ALIST合同研究会ポジションペーパ集    1999.03

  • Langtonの自己増殖ループをもとに構成した構造解消可能型自己増殖ループ

    情報処理学会論文誌[数理モデル化と応用]   40 ( SIG2(TOM1) ) 55 - 67  1999.02

  • Constructing evolutionary systems on a simple deterministic cellular automata space

    Ph.D. Dissertation, Department of Information Science, Graduate School of Science, University of Tokyo    1998.12

  • Constructing evolutionary systems on a simple deterministic cellular automata space

    Ph.D. Dissertation, Department of Information Science, Graduate School of Science, University of Tokyo    1998.12

  • セルラオートマタ上に実装された自己増殖ループの自発的進化

    人工生命研究会 (横浜数理科学セミナー合同)    1998.11

  • Spontaneous evolution of self-reproducing loops implemented on cellular automata

    Artificial Life Workshop (Yokohama Seminar Series on Mathematical Sciences)    1998.11

  • Recent studies on self-replicating structures implemented on cellular automata

    Seminar Note for the 1st ALIST: Artificial Life Independent Seminar in Tokyo    1998.09

  • Recent studies on self-replicating structures implemented on cellular automata

    Seminar Note for the 1st ALIST: Artificial Life Independent Seminar in Tokyo    1998.09

  • Development of Highly -Parallel Simulator of Individuals of Virtual Automata for Verification of "Programmed Self- Decomposition Model" (Special Issue on Parallel Processings)

    SAYAMA Hiroki

    Transactions of Information Processing Society of Japan   39 ( 6 ) 1782 - 1789  1998.06

     View Summary

    "Programmed self-decomposition (PSD) model"is a biological hypothesis proposed in 1987 by T. Oohashi et al. In order to examine how the self-decomposition mechanism effects on the process of reproduction and evolution of life, we developed a highly-parallel simulator of individuals of virtual automata"SIVA-2r"on AP1000+. SIVA-2r was provided with the ability to simulate about 26.2 times as large space within about 1/7.4 as short time as that of the previous simulator implemented on a single workstation. Owing to this improvement, we could simulate a total of 260 cases of large flocks of individuals with various mutation rates and seed values of random numbers within a practial period of time, and also could quantitatively observe the capability of evolutionary adaptation of virtual automata. This article reports on the outline of PSD model, problems and solutions on the development of SIVA-2r, and results of experiment simulated by SIVA-2r.

    CiNii

  • Introduction of Structural Dissolution into Langton's Self-Reproducing Loop

    SAYAMA Hiroki

    IPSJ SIG Notes   98-MPS-19   7 - 12  1998.05

     View Summary

    The phenomenon of death, or disappearance of life, has two aspects.One is failure in the function of life and the other is dissolution of the structure of life.In order to model the latter aspect and examine the significance of it, the author contrived a"structurally dissolvable self-reproducing(SDSR)loop"by introducing the capability of structural dissolution into Langton's self-reproducing(SR)loop[1]in which death as functional failure has already been installed.To be more specific, a dissolving state'8'was introduced into the set of states of the cellular automata(CA)used for embodying the SR loop, besides other modifications to Langton's transition rules.Through this improvement, the SDSR loop can dissolve its own structure when faced with difficult situations such as a shortage of space for self-reproduction.This mechanism(disappearance of a subsystem of the whole system)induces, for the first time, dynamically-stable and potentially evolvable behavior into the colony of SDSR loops.

    CiNii

  • Artificial life based on programmed self-decomposition model

    OOHASHI

    ATR Technical Report   ( TR-H-198 )  1996.07

    CiNii

  • Artificial life based on programmed self-decomposition model

    ATR Technical Report   ( TR-H-198 )  1996.07

  • SIVA: Artificial life based on programmed self-decomposition model

    M.S. Thesis, Department of Information Science, Graduate School of Science, University of Tokyo    1996.02

  • SIVA: Artificial life based on programmed self-decomposition model

    M.S. Thesis, Department of Information Science, Graduate School of Science, University of Tokyo    1996.02

  • プログラムされた自己解体モデルのコンピュータシミュレーション

    佐山弘樹

    第23回数値解析シンポジウム予稿集     67 - 70  1994

    CiNii

  • メディアとしてのBTRONが担う情報の方向性

    TRONWARE(パーソナルメディア刊)   9   90 - 91  1991.06

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