ABSTRACT
Current computational trust models are usually built either on an agent's direct experience of an interaction partner (interaction trust) or reports provided by third parties about their experiences with a partner (witness reputation). However, both of these approaches have their limitations. Models using direct experience often result in poor performance until an agent has had a sufficient number of interactions to build up a reliable picture of a particular partner and witness reports rely on self-interested agents being willing to freely share their experience. To this end, this paper presents Certified Reputation (CR), a novel model of trust that can overcome these limitations. Specifically, CR works by allowing agents to actively provide third-party references about their previous performance as a means of building up the trust in them of their potential interaction partners. By so doing, trust relationships can quickly be established with very little cost to the involved parties. Here we empirically evaluate CR and show that it helps agents pick better interaction partners more quickly than models that do not incorporate this form of trust.
- P. R. Cohen. Empirical Methods for Artificial Intelligence. The MIT Press, 1995. Google ScholarDigital Library
- D. Gambetta. Trust: Making and Breaking Cooperative Relations. Dept. of Sociology, University of Oxford, 2000.Google Scholar
- T. Grandison and M. Sloman. A survey of trust in internet applications. IEEE Comm Surveys & Tutorials, 3(4), 2000. Google ScholarDigital Library
- T. D. Huynh, N. R. Jennings, and N. R. Shadbolt. On handling inaccurate witness reports. In Proc. 8th Int. Workshop on Trust in Agent Societies, pages 63--77, 2005.Google Scholar
- T. D. Huynh, N. R. Jennings, and N. R. Shadbolt. An integrated trust and reputation model for open multi-agent systems. Journal of AAMAS, 2006. (in press). Google ScholarDigital Library
- E. M. Maximilien and M. P. Singh. Reputation and endorsement for web services. ACM SIGEcom Exchanges, 3(1):24--31, 2002. Google ScholarDigital Library
- S. D. Ramchurn, T. D. Huynh, and N. R. Jennings. Trust in multi-agent systems. The Knowledge Engineering Review, 19(1):1--25, March 2004. Google ScholarDigital Library
- J. Sabater. Trust and Reputation for Agent Societies. PhD thesis, Universitat Autònoma de Barcelona, 2003.Google Scholar
- H. Skogsrud, B. Benatallah, and F. Casati. Model-driven trust negotiation for web services. IEEE Internet Computing, 7(6):45--52, 2003. Google ScholarDigital Library
- W. T. L. Teacy, J. Patel, N. R. Jennings, and M. Luck. Coping with inaccurate reputation sources: Experimental analysis of a probabilistic trust model. In Proc. 4th Int Joint Conf on AAMAS, pages 997--1004, 2005. Google ScholarDigital Library
- A. Whitby, A. Jøsang, and J. Indulska. Filtering out unfair ratings in bayesian reputation systems. In Proc. 7th Int Workshop on Trust in Agent Societies, 2004.Google Scholar
- B. Yu and M. P. Singh. Detecting deception in reputation management. In Proc. 2nd Int Joint Conf on Autonomous Agents and Multi-Agent Systems, pages 73--80, 2003. Google ScholarDigital Library
- G. Zacharia and P. Maes. Trust management through reputation mechanisms. Applied Artificial Intelligence, 14(9):881--908, 2000.Google ScholarCross Ref
- P. R. Zimmermann. The Official PGP Users Guide. MIT Press, Cambridge, MA, 1995. Google ScholarDigital Library
Index Terms
- Certified reputation: how an agent can trust a stranger
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