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Modelling Contextualized Reasoning in Complex Societies with "Endorsements"

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  • Shah Jamal Alam

    ()

  • Armando Geller

    ()

  • Ruth Meyer

    ()

  • Bogdan Werth

    ()

Abstract

In many computational social simulation models only cursory reference to the foundations of the agent cognition used is made and computational expenses let many modellers chose simplistic agent cognition architectures. Both choices run counter to expectations framed by scholars active in the domain of rich cognitive modelling that see agent reasoning as socially inherently contextualized. The Manchester school of social simulation proposed a particular kind of a socially contextualized reasoning mechanism, so called endorsements, to implement the cognitive processes underlying agent action selection that eventually causes agent interaction. Its usefulness lies in its lightweight architecture and in taking into account folk psychological conceptions of how reasoning works. These and other advantages make endorsements an amenable tool in everyday social simulation modelling. A yet outstanding comprehensive introduction to the concept of endorsements is provided and its theoretical basis is extended and extant research is critically reviewed. Improvements to endorsements regarding memory and perception are suggested and tested against a case-study.

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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): 4 ()
Pages: 6

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Handle: RePEc:jas:jasssj:2010-30-2

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Keywords: Cognition; Contextualized Reasoning; Evidence-Driven Agent-Based Social Simulation; Empirical Agent-Based Social Simulation; Rich Cognitive Modelling; Tzintzuntzan;

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  1. Robert Axtell & Robert Axelrod & Joshua M. Epstein & Michael D. Cohen, 1995. "Aligning Simulation Models: A Case Study and Results," Working Papers 95-07-065, Santa Fe Institute.
  2. Paul Windrum & Giorgio Fagiolo & Alessio Moneta, 2007. "Empirical Validation of Agent-Based Models: Alternatives and Prospects," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 10(2), pages 8.
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Cited by:
  1. Daigneault, Adam J. & Morgan, Fraser, 2012. "Estimating Impacts of Climate Change Policy on Land Use: An Agent Based Modeling Approach," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124973, Agricultural and Applied Economics Association.

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