A Protocol for a Distributed Recommender System

  • José M. Vidal
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3577)

Abstract

We present a domain model and protocol for the exchange of recommendations by selfish agents without the aid of any centralized control. Our model captures a subset of the realities of recommendation exchanges in the Internet. We provide an algorithm that selfish agents can use for deciding whether to exchange recommendations and with whom. We analyze this algorithm and show that, under certain common circumstances, the agents’ rational choice is to exchange recommendations. Finally, we have implemented our model and algorithm and tested the performance of various populations. Our results show that both the social welfare and the individual utility of the agents is increased by participating in the exchange of recommendations.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Resnick, P., Varian, H.R.: Recommender systems. Communications of the ACM 40, 56–58 (1997)CrossRefGoogle Scholar
  2. 2.
    Fagin, R., Halpern, J.Y., Moses, Y., Vardi, M.Y.: Reasoning About Knowledge. The MIT Press, Cambridge (1995)MATHGoogle Scholar
  3. 3.
    Axelrod, R.M.: The Evolution of Cooperation. Basic Books, Newyork (1984)Google Scholar
  4. 4.
    Wilensky, U.: NetLogo: Center for connected learning and computer-based modeling. Northwestern University, Evanston (1999), http://ccl.northwestern.edu/netlogo/ Google Scholar
  5. 5.
    Terveen, L., Hill, W., Amento, B., McDonald, D., Creter, J.: Phoaks: a system for sharing recommendations. Communications of the ACM 40, 59–62 (1997)CrossRefGoogle Scholar
  6. 6.
    Kautz, H., Selman, B., Shah, M.: Referral web: combining social networks and collaborative filtering. Communications of the ACM 40, 63–65 (1997)CrossRefGoogle Scholar
  7. 7.
    Foner, L.N.: Yenta: A multi-agent, referral based matchmaking system. In: Proceedings of The First International Conference on Autonomous Agents (1997)Google Scholar
  8. 8.
    Avery, C., Resnick, P., Zeckhauser, R.: The market for evaluations. The American Economic Review 89, 484–564 (1999)CrossRefGoogle Scholar
  9. 9.
    Gong, L.: JXTA: A network programming environment. IEEE Internet Computing 5, 88–95 (2001)CrossRefGoogle Scholar
  10. 10.
    Oram, A. (ed.): Peer-to-Peer. O’Reilly, Sebastopol (2001)Google Scholar
  11. 11.
    Adar, E., Huberman, B.A.: Free riding on gnutella. First Monday (2000)Google Scholar
  12. 12.
    Yu, B., Singh, M.P.: An evidential model of distributed reputation management. In: Proceedings of the 1st International Joint Conference on Autonomous Agents and MultiAgent Systems, pp. 294–301 (2002)Google Scholar
  13. 13.
    Yu, B., Singh, M.P.: Distributed reputation management for electronic commerce. Computational Intelligence 18, 535–549 (2002)CrossRefMathSciNetGoogle Scholar
  14. 14.
    Yu, B., Singh, M.P., Sycara, K.: Developing trust in large-scale peer-to-peer systems. In: Proceedings of First IEEE Symposium on Multi-Agent Security and Survivability, pp. 1–10 (2004)Google Scholar
  15. 15.
    Henry, E., Kyburg, J.: Bayesian and non-bayesian evidential updating. Artificial Intelligence 31, 271–293 (1987)MATHCrossRefMathSciNetGoogle Scholar
  16. 16.
    Yu, B., Li, C., Singh, M.P., Sycara, K.: A dynamic pricing mechanism for p2p referral systems. In: Proceedings of Third International Joint Conference on Autonomous Agents and Multi-Agent Systems, pp. 1426–1427 (2004)Google Scholar
  17. 17.
    Wei, Y.Z., Moreau, L., Jennings, N.R.: Recommender systems: a market-based design. In: Proceedings of the second international joint conference on Autonomous agents and multiagent systems, pp. 600–607. ACM Press, New York (2003)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • José M. Vidal
    • 1
  1. 1.University of South CarolinaColumbiaUSA

Personalised recommendations