TRUST!-A distributed multi-agent system for community formation and information recommendation

In centralized collaborative information recommendation, there is a bottleneck for the scalability and the availability. Yenta is a decentralized approach. Information can be recommended through the clustering. The clustering of similar agents in Yenta is based on the similarities between the content of their interest models. So the agents must represent the interests of users or the models of other agents in the same way. This paper introduces the TRUST! system. In TRUST!, the agent´s user evaluates the information recommended from other agents. The trust degree between different agents is decided by the user´s evaluation. The similarities between different agents are measured by the trust connections. So the agents can represent the interests of users or the models of other agents in different ways. TRUST! is a distributed multiagent system for Internet information propagation and recommendation. It is based on limited friends list and trust relationship. To update trust, we introduce the PID (proportion, integral, and differential coefficient) arithmetic. Through emulation experiments, we give some analysis of the distributed clustering