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Understanding Complex Social Dynamics: a Plea for Cellular Automata Based Modelling

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The article argues that using cellular automata (CA) is a promising modelling approach to understand social dynamics. The first section introduces and illustrates the concept of CA. Section 2 gives a short history of CA in the social sciences. Section 3 describes and analyses a more complicated model of evolving support networks. The final section summarises the advantages of the CA approach.

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  • Andreas Flache & Rainer Hegselmann, 1998. "Understanding Complex Social Dynamics: a Plea for Cellular Automata Based Modelling," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 1(3), pages 1-1.
    • Handle: RePEc:jas:jasssj:1998-5-1
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    1. Kirchkamp, Oliver, 2000. "Spatial evolution of automata in the prisoners' dilemma," Journal of Economic Behavior & Organization, Elsevier, vol. 43(2), pages 239-262, October.
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    3. Schelling, Thomas C, 1969. "Models of Segregation," American Economic Review, American Economic Association, vol. 59(2), pages 488-493, May.
    4. Joshua M. Epstein & Robert L. Axtell, 1996. "Growing Artificial Societies: Social Science from the Bottom Up," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262550253, December.
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    6. Andreas Koulouris & Ioannis Katerelos & Theodore Tsekeris, 2013. "Multi-Equilibria Regulation Agent-Based Model of Opinion Dynamics in Social Networks," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, vol. 11(1), pages 51-70.
    7. Hendrikse, G.W.J. & Smit, R., 2007. "On the Evolution of Product Portfolio Coherence of Cooperatives versus Corporations: An Agent-Based Analysis of the Single Origin Constraint," ERIM Report Series Research in Management ERS-2007-055-ORG, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
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    13. Bithell, M. & Macmillan, W.D., 2007. "Escape from the cell: Spatially explicit modelling with and without grids," Ecological Modelling, Elsevier, vol. 200(1), pages 59-78.
    14. Nicole J. Saam & Andreas G. Harrer, 1999. "Simulating Norms, Social Inequality, and Functional Change in Artificial Societies," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 2(1), pages 1-2.
    15. Schweitzer, Frank & Zimmermann, Jörg & Mühlenbein, Heinz, 2002. "Coordination of decisions in a spatial agent model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 303(1), pages 189-216.
    16. Andreas Flache, 2001. "Individual Risk Preferences And Collective Outcomes In The Evolution Of Exchange Networks," Rationality and Society, , vol. 13(3), pages 304-348, August.
    17. Malte Schwoon, 2006. "Simulating the adoption of fuel cell vehicles," Journal of Evolutionary Economics, Springer, vol. 16(4), pages 435-472, October.
    18. Rainer Hegselmann & Ulrich Krause, 2002. "Opinion Dynamics and Bounded Confidence Models, Analysis and Simulation," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 5(3), pages 1-2.
    19. Werner Güth & Hartmut Kliemt & Stefan Napel, "undated". "Wie Du mir, so ich Dir! - Ökonomische Theorie und Experiment am Beispiel der Reziprozität," Papers on Strategic Interaction 2002-19, Max Planck Institute of Economics, Strategic Interaction Group.
    20. Deng, W. & Hendrikse, G.W.J., 2022. "On the Evolution of Product Portfolio of Cooperatives versus IOFs: An Agent-Based Analysis of the Single Origin Constraint," ERIM Report Series Research in Management ERS-2022-005-ORG, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    21. Andreas Flache & Rainer Hegselmann, 1999. "Rationality vs. Learning in the Evolution of Solidarity Networks: A Theoretical Comparison," Computational and Mathematical Organization Theory, Springer, vol. 5(2), pages 97-127, July.

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