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Ontology, a Mediator for Agent-Based Modeling in Social Science

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  • Pierre Livet

    ()

  • Jean-Pierre Muller

    ()

  • Denis Phan

    ()

  • Lena Sanders

    ()

Abstract

Agent-Based Models are useful to describe and understand social, economic and spatial systems\' dynamics. But, beside the facilities which this methodology offers, evaluation and comparison of simulation models are sometimes problematic. A rigorous conceptual frame needs to be developed. This is in order to ensure the coherence in the chain linking at the one extreme the scientist\'s hypotheses about the modeled phenomenon and at the other the structure of rules in the computer program. This also systematizes the model design from the thematician conceptual framework as well. The aim is to reflect upon the role that a well defined ontology, based on the crossing of the philosophical and the computer science insights, can play to solve such questions and help the model building. We analyze different conceptions of ontology, introduce the \'ontological test\' and show its usefulness to compare models. Then we focus on the model building and show the place of a systematic ABM ontology. The latter process is situated within a larger framework called the \'knowledge framework\' in which not only the ontologies but also the notions of theory, model and empirical data take place. At last the relation between emergence and ontology is discussed.

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File URL: http://jasss.soc.surrey.ac.uk/13/1/3/3.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: 3

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Handle: RePEc:jas:jasssj:2009-29-2

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Keywords: Ontology; Agent-Based Computational Economic; Agent-Based Model of Simulation; Model Design; Model Building; Knowledge Framework; Spatial Simulation; Social Simulation; Ontological Test;

References

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  1. Jean Louis Dessalles & Denis Phan, 2005. "Emergence in multi-agent systems:Cognitive hierarchy, detection, and complexity reduction," Computing in Economics and Finance 2005, Society for Computational Economics 257, Society for Computational Economics.
  2. 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, Journal of Artificial Societies and Social Simulation, vol. 13(1), pages 5.
  3. 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.
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