• DocumentCode
    2270698
  • Title

    Believing others: pro and cons

  • Author

    Sen, Sandip ; Biswas, Anish ; Debnath, Sandip

  • Author_Institution
    Dept. of Math. & Comput. Sci., Tulsa Univ., OK, USA
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    279
  • Lastpage
    285
  • Abstract
    Under the assumption that agents remain in the system for significant time periods, or that the agent composition changes only slowly Sen (1996) has previously presented a prescriptive strategy for promoting and sustaining cooperation among self-interested agents. The adaptive, probabilistic policy prescribed promotes reciprocative cooperation that improves both individual and group performance in the long run. In the short run, however, selfish agents could still exploit reciprocative agents. In this paper we evaluate the hypothesis that the exploitative tendencies of selfish agents can be effectively curbed if reciprocative agents share their “opinions” of other agents. Since the true nature of agents are not known a priori and is learned from experience, believing others can also pose other hazards. We provide a learned trust-based evaluation function that is shown to resist both individual and concerted deception on the part of selfish agents
  • Keywords
    belief maintenance; learning by example; multi-agent systems; probability; belief maintenance; learning from experience; multiple agent systems; prescriptive strategy; probability; reciprocative cooperation; selfish agents; Centralized control; Cost accounting; Electronic commerce; Environmental economics; Hazards; Humans; Open systems; Problem-solving; Recommender systems; Resists;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    MultiAgent Systems, 2000. Proceedings. Fourth International Conference on
  • Conference_Location
    Boston, MA
  • Print_ISBN
    0-7695-0625-9
  • Type

    conf

  • DOI
    10.1109/ICMAS.2000.858464
  • Filename
    858464