Propagation of trust and distrust
Proceedings of the 13th international conference on World Wide Web
ACM Transactions on Internet Technology (TOIT)
Sybilproof reputation mechanisms
Proceedings of the 2005 ACM SIGCOMM workshop on Economics of peer-to-peer systems
Sybilproof transitive trust protocols
Proceedings of the 10th ACM conference on Electronic commerce
Quantifying incentive compatibility of ranking systems
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
An axiomatic approach to personalized ranking systems
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
On the axiomatic foundations of ranking systems
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Manipulation-resistant reputations using hitting time
WAW'07 Proceedings of the 5th international conference on Algorithms and models for the web-graph
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Establishing trust amongst agents is of central importance to the development of well-functioning multi-agent systems. For example, the anonymity of transactions on the Internet can lead to inefficiencies; e.g., a seller on eBay failing to ship a good as promised, or a user free-riding on a file-sharing network. Trust (or reputation) mechanisms can help by aggregating and sharing trust information between agents. Unfortunately these mechanisms can often be manipulated by strategic agents. Existing mechanisms are either very robust to manipulation (i.e., manipulations are not beneficial for strategic agents), or they are very informative (i.e., good at aggregating trust data), but never both. This paper explores this trade-off between these competing desiderata. First, we introduce a metric to evaluate the informativeness of existing trust mechanisms. We then show analytically that trust mechanisms can be combined to generate new hybrid mechanisms with intermediate robustness properties. We establish through simulation that hybrid mechanisms can achieve higher overall efficiency in environments with risky transactions and mixtures of agent types (some cooperative, some malicious, and some strategic) than any previously known mechanism.