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A Methodology for Complex Social Simulations

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    Abstract

    Social simulation - an emerging field of computational social science - has progressed from simple toy models to increasingly realistic models of complex social systems, such as agent-based models where heterogeneous agents interact with changing natural or artificial environments. These larger, multidisciplinary projects require a scientific research methodology distinct from, say, simpler social simulations with more limited scope, intentionally minimal complexity, and typically under a single investigator. This paper proposes a methodology for complex social simulations - particularly inter- and multi-disciplinary socio-natural systems with multi-level architecture - based on a succession of models akin to but distinct from the late Imre Lakatos' notion of a 'research programme'. The proposed methodology is illustrated through examples from the Mason-Smithsonian project on agent-based models of the rise and fall of polities in Inner Asia. While the proposed methodology requires further development, so far it has proven valuable for advancing the scientific objectives of the project and avoiding some pitfalls.

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    File URL: http://jasss.soc.surrey.ac.uk/13/1/7/7.pdf
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    Bibliographic Info

    Article provided by Journal of Artificial Societies and Social Simulation in its journal Journal of Artificial Societies and Social Simulation.

    Volume (Year): 13 (2010)
    Issue (Month): 1 ()
    Pages: 7

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    Handle: RePEc:jas:jasssj:2009-21-2

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    Keywords: Agent-Based Modeling Methodology; M2M; Social Simulation; Computational Social Science; Social Complexity; Inner Asia;

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    1. Schelling, Thomas C, 1969. "Models of Segregation," American Economic Review, American Economic Association, American Economic Association, vol. 59(2), pages 488-93, May.
    2. David Hales & Juliette Rouchier & Bruce Edmonds, 2003. "Model-To-Model Analysis," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 6(4), pages 5.
    3. Juliette Rouchier & Claudio Cioffi-Revilla & J. Gary Polhill & Keiki Takadama, 2008. "Progress in Model-To-Model Analysis," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 11(2), pages 8.
    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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    Cited by:
    1. Nina Schwarz & Daniel Kahlenberg & Dagmar Haase & Ralf Seppelt, 2012. "ABMland - a Tool for Agent-Based Model Development on Urban Land Use Change," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 15(2), pages 8.

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