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  • 标题:Modelling Contextualized Reasoning in Complex Societies with "Endorsements"
  • 本地全文:下载
  • 作者:Shah Jamal Alam ; Armando Geller ; Ruth Meyer
  • 期刊名称:Journal of Artificial Societies and Social Simulation
  • 印刷版ISSN:1460-7425
  • 出版年度:2010
  • 卷号:13
  • 期号:4
  • 页码:1-30
  • DOI:10.18564/jasss.1667
  • 出版社:University of Surrey, Department of Sociology
  • 摘要: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.
  • 关键词:Cognition; Contextualized Reasoning; Evidence-Driven Agent-Based Social Simulation; Empirical Agent-Based Social Simulation; Rich Cognitive Modelling; Tzintzuntzan
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