A reputation model framework for artificial societies: a case study in child vehicle safety simulation

  • Authors:
  • Ziad Kobti;Shamual Rahaman;Anne W. Snowdon;Robert D. Kent

  • Affiliations:
  • School of Computer Science, University of Windsor, Windsor, Ontario, Canada;School of Computer Science, University of Windsor, Windsor, Ontario, Canada;Odette School of Business, University of Windsor, Windsor, Ontario, Canada;School of Computer Science, University of Windsor, Windsor, Ontario, Canada

  • Venue:
  • Canadian AI'08 Proceedings of the Canadian Society for computational studies of intelligence, 21st conference on Advances in artificial intelligence
  • Year:
  • 2008

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Abstract

Formalizing reputation into a complex social model poses significant challenges, mainly due to its distinct social nature. In this paper we introduce the notion of reputation into the child vehicle safety simulation. From a health and safety perspective, the aim of the model is to reduce injury in children by minimizing incorrect usage of child vehicle constraints by influencing driver behaviour. A cultural framework was previously established to enable external injection of knowledge, or intervention, into the artificial society. A dynamic social network allowed the acquisition, and subsequent exchange and evolution of knowledge. We hypothesize that selective intervention criteria would achieve better system convergence. We consequently introduce reputation to be a viable selection criterion. We establish a generic reputation framework that would allow us to test alternate formalizations of reputation models. We report on the generic framework design and three initial reputation models with their respective comparative performance and potential to improve the intervention outcome.