skip to main content
10.1145/544741.544809acmconferencesArticle/Chapter ViewAbstractPublication PagesaamasConference Proceedingsconference-collections
Article

An evidential model of distributed reputation management

Published:15 July 2002Publication History

ABSTRACT

For agents to function effectively in large and open networks, they must ensure that their correspondents, i.e., the agents they interact with, are trustworthy. Since no central authorities may exist, the only way agents can find trustworthy correspondents is by collaborating with others to identify those whose past behavior has been untrustworthy. In other words, finding trustworthy correspondents reduces to the problem of distributed reputation management.Our approach adapts the mathematical theory of evidence to represent and propagate the ratings that agents give to their correspondents. When evaluating the trustworthiness of a correspondent, an agent combines its local evidence (based on direct prior interactions with the correspondent) with the testimonies of other agents regarding the same correspondent. We experimentally studied this approach to establish that some important properties of trust are captured by it.

References

  1. A. Abdul-Rahman and S. Hailes. Supporting trust in virtual communities. In Proceedings of the 33rd Hawaii International Conference on Systems Science, 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. K. Aberer and Z. Despotovic. Managing trust in a peer-2-peer information system. In Proceedings of the 10th International Conference on Information and Knowledge Management (CIKM), pages 310--317, 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. R. Axelrod. The Evolution of Cooperation. Basic Books, New York, 1984.Google ScholarGoogle Scholar
  4. K. S. Barber and J. Kim. Belief revision process based on trust: Simulation experiments. In Proceedings of Autonomous Agents '01 Workshop on Deception, Fraud, and Trust in Agent Societies, pages 1--12, May 2001.Google ScholarGoogle Scholar
  5. R. Boyd and J. P. Borderbaum. No pure strategy is evolutionary stable in the repeated prisoner's dilemma game. Nature, 327:58--59, 1987.Google ScholarGoogle ScholarCross RefCross Ref
  6. C. Castelfranchi. Modelling social action for AI agents. Artificial Intelligence, 103:157--182, 1998. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. C. Castelfranchi and R. Falcone. Principle of trust for MAS: cognitive anatomy, social importance, and quantification. In Proceedings of 3rd International Conference on MultiAgent Systems, pages 72--79, 1998. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. A. Chavez and P. Maes. Kasbah: An agent marketplace for buying and selling goods. In Proceedings of the 1st International Conference on the Practical Application of Intelligent Agents and Multiagent Technology (PAAM), pages 75--90, 1996.Google ScholarGoogle Scholar
  9. L. Foner. Yenta: A multi-agent, referral-based matchmaking system. In Proceedings of the 1st International Conference on Autonomous Agents, pages 301--307, 1997. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. L. Gasser. Social conceptions of knowledge and action: DAI foundations and open systems semantics. Artificial Intelligence, 47:107--138, 1991. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. J. Gordon and E. H. Shortliffe. A method for managing evidential reasoning in a hierarchical hypothesis space. Artificial Intelligence, 26:323--357, 1985. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. D. Heckerman. Probabilistic interpretations for MYCIN's certainty factors. In Uncertainty in Artificial Intelligence, pages 167--196, 1986.Google ScholarGoogle ScholarCross RefCross Ref
  13. H. Kautz, B. Selman, and A. Milewski. Agent amplified communication. In Proceedings of the Thirteenth National Conference on Artificial Intelligence, pages 3--9, 1996. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. R. Khare and A. Rifkin. Weaving a web of trust. World Wide Web, 2(3):77--112, 1997. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. H. E. Kyburg. Bayesian and non-bayesian evidential updating. Artificial Intelligence, 31:271--293, 1987. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. S. P. Marsh. Formalising Trust as a Computational Concept. PhD thesis, Department of Computing Science and Mathematics, University of Stirling, Apr. 1994.Google ScholarGoogle Scholar
  17. J. Pearl. Probabilistic Reasoning in Intelligent Systems: Network of Plausible Inference. Morgan Kaufmann Publishers Inc., San Mateo, California, 1988. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. M. Prietula and K. M. Carley. Exploring the effects of agent trust and benevolence in a simulated organization task. Applied Artificial Intelligence, 13:321--338, 1999.Google ScholarGoogle ScholarCross RefCross Ref
  19. T. Rea and P. Skevington. Engendering trust in electronic commerce. British Telecommunications Engineering, 17(3):150--157, 1998.Google ScholarGoogle Scholar
  20. M. Schillo and P. Funk. Who can you trust: Dealing with deception. In Proceedings of the Autonomous Agents Workshop on Deception, Fraud and Trust in Agent Societies, pages 95--106, 1999.Google ScholarGoogle Scholar
  21. M. Schillo, P. Funk, and M. Rovatsos. Using trust for detecting deceitful agents in artificial societies. Applied Artificial Intelligence, 14:825--848, 2000.Google ScholarGoogle ScholarCross RefCross Ref
  22. G. Shafer. A Mathematical Theory of Evidence. Princeton University Press, Princeton, NJ, 1976.Google ScholarGoogle Scholar
  23. S. P. Shapiro. The social control of impersonal trust. The American Journal of Sociology, 93(3):623--658, 1987.Google ScholarGoogle ScholarCross RefCross Ref
  24. M. P. Singh, B. Yu, and M. Venkatraman. Community-based service location. Communications of the ACM, 44(4):49--54, 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. D. J. Watts and S. H. Strogatz. Collective dynamics of `small-world' networks. Nature, 393:440--442, June 1998.Google ScholarGoogle ScholarCross RefCross Ref
  26. B. Yu and M. P. Singh. A social mechanism of reputation management in electronic communities. In Proceedings of the 4th International Workshop on Cooperative Information Agents, pages 154--165, 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. B. Yu and M. P. Singh. Trust and reputation management in a small-world network. In Proceedings of the 4th International Conference on MultiAgent Systems, pages 449--450, 2000. Poster. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. G. Zacharia and P. Maes. Trust management through reputation mechanisms. Applied Artificial Intelligence, 14:881--908, 2000.Google ScholarGoogle ScholarCross RefCross Ref

Index Terms

  1. An evidential model of distributed reputation management

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in
    • Published in

      cover image ACM Conferences
      AAMAS '02: Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 1
      July 2002
      540 pages
      ISBN:1581134800
      DOI:10.1145/544741

      Copyright © 2002 ACM

      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 15 July 2002

      Permissions

      Request permissions about this article.

      Request Permissions

      Check for updates

      Qualifiers

      • Article

      Acceptance Rates

      Overall Acceptance Rate1,155of5,036submissions,23%

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader