Enhancing Trust-Based Competitive Multi-Agent Systems by Certified Reputation

In the past, the experience of the ART community highlighted that, in absence of information about the quality of the recommendation providers, it is better to exploit only the direct knowledge about the environment (i.e., a reliability measure), missing the reputation measure. However, when the size of the agent space becomes large enough and the number of ``expert'' agents to contact is small, the use of just the reliability is little effective. Unfortunately, the largeness of the agent space makes the problem of the trustworthiness of recommendations very critical, so that the combination of reliability and reputation is not a trivial task. In this paper, we deal with the above problem by studying how the introduction of the notion of certified reputation, and its exploitation to combine reputation and reliability, can improve the performance of an agent in a competitive MAS context. We analyze different populations, using the standard platform ART, highlighting a significant positive impact and providing very interesting results.