by Sandip Sen, Neelima Sajja
In AAMAS ’02: Proceedings of the first international joint conference on Autonomous agents and multiagent systems
http://www.mcs.utulsa.edu/~sandip/aamas02-trust.ps
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Abstract:
We consider the problem of user agents selecting processor agents to processor tasks. We assume that processor agents are drawn from two populations: high and low-performing processors with di#erent averages but similar variance in performance. For selecting a processor, a user agent queries other user agents for their high/low rating of di#erent processors. We assume that a known percentage of "liar " users, who give inverse estimates of processors. We develop a trust mechanism that determines the number of users to query given a target guarantee threshold likelihood of choosing high-performance processors in the face of such "noisy " reputation mechanisms. We evaluate the robustness of this reputation-based trusting mechanism over varying environmental parameters like percentage of liars, performance difference and variances for high and low-performing agents, learning rates, etc. 1.
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