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

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Abstract

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.

Suggested Citation

  • 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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    File URL: http://jasss.soc.surrey.ac.uk/1/3/1/1.pdf
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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.
    2. Keenan, Donald C. & O'Brien, Mike J., 1993. "Competition, collusion, and chaos," Journal of Economic Dynamics and Control, Elsevier, vol. 17(3), pages 327-353, May.
    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, January.
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    Cited by:

    1. Marco A. Janssen & Wander Jager, 1999. "An Integrated Approach to Simulating Behavioural Processes: a Case Study of the Lock-in of Consumption Patterns," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 2(2), pages 1-2.
    2. Desmarchelier, Benoît & Djellal, Faridah & Gallouj, Faïz, 2013. "Environmental policies and eco-innovations by service firms: An agent-based model," Technological Forecasting and Social Change, Elsevier, vol. 80(7), pages 1395-1408.
    3. Francesc S. Beltran & Salvador Herrando & Doris Ferreres & Marc-Antoni Adell & Violant Estreder & Marcos Ruiz-Soler, 2009. "Forecasting a Language Shift Based on Cellular Automata," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(3), pages 1-5.
    4. 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.
    5. 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.
    6. Adam Douglas Henry & Bjoern Vollan, 2012. "Risk, Networks, and Ecological Explanations for the Emergence of Cooperation in Commons Governance," Rationality, Markets and Morals, Frankfurt School Verlag, Frankfurt School of Finance & Management, vol. 3(59), October.
    7. Luis R. Izquierdo & Segismundo S. Izquierdo & José Manuel Galán & José Ignacio Santos, 2009. "Techniques to Understand Computer Simulations: Markov Chain Analysis," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(1), pages 1-6.
    8. Matthew Jarman & Andrzej Nowak & Wojciech Borkowski & David Serfass & Alexander Wong & Robin Vallacher, 2015. "The Critical Few: Anticonformists at the Crossroads of Minority Opinion Survival and Collapse," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(1), pages 1-6.
    9. repec:eee:ecomod:v:200:y:2007:i:1:p:59-78 is not listed on IDEAS
    10. 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.
    11. 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.
    12. Malte Schwoon, 2006. "Simulating the adoption of fuel cell vehicles," Journal of Evolutionary Economics, Springer, vol. 16(4), pages 435-472, October.
    13. 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.
    14. 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.

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    Keywords

    Cellular Automata; Social Dynamics; Modelling;

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