Abstract-In agent-based systems, agents can be organized within groups, called communities, where members are providing similar or complementary services. Agentbased communities of web services is an example of such systems. Managing reputation of each agent and of the whole community is a key issue towards securing this type of systems, where a controller agent is designed to observe and check the behavior of each member to update and maintain the system's reputation. Scheduling the maintenance activity by deciding about the moment where the check has to be done is still an open problem. Because it is highly expensive, maintenance cannot be done every moment or based on small history of agents' behaviors. We propose in this paper a scheduling algorithm that helps the controller agent improve the quality of the reputation mechanism, which increases the trust value of users toward the community. The proposed algorithm is based on a class of games called Bayesian Stackelberg. Our Bayesian Stackelberg game is designed between the controller agent and community members, for example agent-based web services. We simulate and compare the efficiency of our algorithm with other stochastic techniques, namely uniform, normal and Poisson distributions. This research draws the lines for future work in the subject of optimizing reputation mechanisms through maintenance in different time intervals.
Mohamed Amine M'hamdi et al. REF proposed a scheduling algorithm to help the controller agent improve the quality of the reputation mechanism.
Scheduling Reputation Maintenance in Agent-based Communities Using Game Theory
JSW
JSW
Computer Science