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Author Sen, Sandip ♦ Sajja, Neelima
Source CiteSeerX
Content type Text
Publisher ACM Press
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Processor Agent ♦ Di Erent Processor ♦ Low-performing Processor ♦ Trust Mechanism ♦ High Low Rating ♦ Di Erent Average ♦ Reputation-based Trusting Mechanism ♦ User Agent ♦ Target Guarantee ♦ Inverse Estimate ♦ Boolean Case ♦ High-performance Processor ♦ Environmental Parameter ♦ Noisy Reputation Mechanism ♦ Low-performing Agent ♦ Known Percentage ♦ Similar Variance ♦ Reputation-based Trust ♦ Performance Difference
Description 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.
In Proceedings of the 1st International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article
Publisher Date 2002-01-01