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Logic-Based Reputation Model in E-Commerce Simulation



We employ a multimodal logic in a decision making mechanism involving trust and reputation. The mechanism is then used in a community of interacting agents which develop cooperative relationships, assess the results against several quality criteria and possibly publish their beliefs inside the group. A new definition is proposed for describing how an agent deals with the common reputation information and with divergent opinions. The definition permits selecting and integrating the knowledge obtained from the peers, based on their perceived trust, as well as on threshold called critical mass. The influence of this parameter and of the number of agents supporting a sentence over its adoption are then investigated.

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  • Ioan Alfred Letia & Radu Razvan Slavescu, 2012. "Logic-Based Reputation Model in E-Commerce Simulation," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 15(3), pages 1-7.
  • Handle: RePEc:jas:jasssj:2012-17-2

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    References listed on IDEAS

    1. Matteo Richiardi & Roberto Leombruni & Nicole J. Saam & Michele Sonnessa, 2006. "A Common Protocol for Agent-Based Social Simulation," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 9(1), pages 1-15.
    2. Ulrich Frank & Klaus G. Troitzsch, 2005. "Epistemological Perspectives on Simulation," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 8(4), pages 1-7.
    3. Janssen, Marco & de Vries, Bert, 1998. "The battle of perspectives: a multi-agent model with adaptive responses to climate change," Ecological Economics, Elsevier, vol. 26(1), pages 43-65, July.
    4. Hanneman & Anthony Patrick, 1997. "On the Uses of Computer-Assisted Simulation Modeling in the Social Sciences," Sociological Research Online, Sociological Research Online, vol. 2(2), pages 1-5.
    5. Karolina SafarzyƄska & Jeroen Bergh, 2010. "Evolutionary models in economics: a survey of methods and building blocks," Journal of Evolutionary Economics, Springer, vol. 20(3), pages 329-373, June.
    6. Giorgio Fagiolo & Alessio Moneta & Paul Windrum, 2007. "A Critical Guide to Empirical Validation of Agent-Based Models in Economics: Methodologies, Procedures, and Open Problems," Computational Economics, Springer;Society for Computational Economics, vol. 30(3), pages 195-226, October.
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    Cited by:

    1. Davide Secchi & Raffaello Seri, 2017. "Controlling for false negatives in agent-based models: a review of power analysis in organizational research," Computational and Mathematical Organization Theory, Springer, vol. 23(1), pages 94-121, March.


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