Learning trust strategies in reputation exchange networks

An agent's trust decision strategy consists of the agent's policies for making trust-related decisions, such as who to trust, how trustworthy to be, what reputations to believe, and when to tell truthful reputations. In reputation exchange networks, learning trust decision strategies is complex, compared to non-reputationcommunicating systems. When potential partners may exchange reputation information about an agent, the agent's interactions with one partner are no longer independent from interactions with another; partners may tell each other about their experiences with the agent, influencing future behavior. This research enumerates the types of decisions an agent faces in reputation exchange networks, explains the interdependencies between these decisions, and correlates rewards to each decision. Experimental results using the Agent Reputation and Trust (ART) Testbed demonstrate the success of strategy-learning agents over agents employing naive strategies. The var...

• Type: Conference
• Year: 2006
• Where: ATAL
• Authors: Karen Fullam, K. Suzanne Barber
• Keywords: Agent's Trust Decision, ATAL 2006, Intelligent Agents, Reputation Exchange Networks, Trust Decisions