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Agent-Based Models and Simulations in Economics and Social Sciences: From Conceptual Exploration to Distinct Ways of Experimenting

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Abstract

Now that complex Agent-Based Models and computer simulations spread over economics and social sciences - as in most sciences of complex systems -, epistemological puzzles (re)emerge. We introduce new epistemological concepts so as to show to what extent authors are right when they focus on some empirical, instrumental or conceptual significance of their model or simulation. By distinguishing between models and simulations, between types of models, between types of computer simulations and between types of empiricity obtained through a simulation, section 2 gives the possibility to understand more precisely - and then to justify - the diversity of the epistemological positions presented in section 1. Our final claim is that careful attention to the multiplicity of the denotational powers of symbols at stake in complex models and computer simulations is necessary to determine, in each case, their proper epistemic status and credibility.

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  • Denis Phan & Franck Varenne, 2010. "Agent-Based Models and Simulations in Economics and Social Sciences: From Conceptual Exploration to Distinct Ways of Experimenting," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 13(1), pages 1-5.
  • Handle: RePEc:jas:jasssj:2009-23-2
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    1. Denis Phan & Franck Varenne, 2010. "Agent-Based Models and Simulations in Economics and Social Sciences: From Conceptual Exploration to Distinct Ways of Experimenting," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 13(1), pages 1-5.
    2. Uskali Maki, 2005. "Models are experiments, experiments are models," Journal of Economic Methodology, Taylor & Francis Journals, vol. 12(2), pages 303-315.
    3. Mary Morgan, 2005. "Experiments versus models: New phenomena, inference and surprise," Journal of Economic Methodology, Taylor & Francis Journals, vol. 12(2), pages 317-329.
    4. Tesfatsion, Leigh, 2002. "Agent-Based Computational Economics: Growing Economies from the Bottom Up," ISU General Staff Papers 200201010800001251, Iowa State University, Department of Economics.
    5. Leigh Tesfatsion, 2002. "Agent-Based Computational Economics," Computational Economics 0203001, University Library of Munich, Germany, revised 15 Aug 2002.
    6. Robert Axelrod, 1997. "Advancing the Art of Simulation in the Social Sciences," Working Papers 97-05-048, Santa Fe Institute.
    7. Pierre Livet & Denis Phan & Lena Sanders, 2008. "Why do we need Ontology for Agent-Based Models?," Lecture Notes in Economics and Mathematical Systems, in: Klaus Schredelseker & Florian Hauser (ed.), Complexity and Artificial Markets, chapter 11, pages 133-145, Springer.
    8. 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, vol. 6(4), pages 1-5.
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    1. Denis Phan & Franck Varenne, 2010. "Agent-Based Models and Simulations in Economics and Social Sciences: From Conceptual Exploration to Distinct Ways of Experimenting," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 13(1), pages 1-5.
    2. Pierre Livet & Jean-Pierre Muller & Denis Phan & Lena Sanders, 2010. "Ontology, a Mediator for Agent-Based Modeling in Social Science," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 13(1), pages 1-3.
    3. Fontana, Magda, 2010. "Can neoclassical economics handle complexity? The fallacy of the oil spot dynamic," Journal of Economic Behavior & Organization, Elsevier, vol. 76(3), pages 584-596, December.

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