Reputation and social network analysis in multi-agent systems
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 1
Eliciting Informative Feedback: The Peer-Prediction Method
Management Science
Obtaining reliable feedback for sanctioning reputation mechanisms
Journal of Artificial Intelligence Research
Mechanisms for making crowds truthful
Journal of Artificial Intelligence Research
Taxonomy of trust: Categorizing P2P reputation systems
Computer Networks: The International Journal of Computer and Telecommunications Networking - Management in peer-to-peer systems
Incentive-based robust reputation mechanism for p2p services
OPODIS'06 Proceedings of the 10th international conference on Principles of Distributed Systems
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Open and autonomous environments, such as peer to peer networks or many social networks, are efficient only if cooperation among nodes is ensured. In order to ensure cooperative behavior, we have added a new node type to the system, called inspector and used game theoretical tools to analyze the system. Inspectors punish both misbehaving nodes as well as nodes who provide dishonest ratings about other peers. Analyzing the proposed inspection game ensures that corruption of inspectors and misbehavior of nodes is bounded. The game enables the system designer to set the amount of corruption that is allowed according to the budget.