In shared competitive environments, where information comes from various sources, agents may interact with each other in a competitive manner in order to achieve their individual goals. Numerous research efforts exist, attempting to define protocols, rules and interfaces for agents to abide by and ensure trustworthy exchange of information. Auction environments and e-commerce platforms are such paradigms, where trust and reputation are vital factors determining agent strategy. And though the process is always secured with a number of safeguards, there is always the issue of unreliability. In this context, the Agent Reputation and Trust (ART) testbed has provided researchers with the ability to test different trust and reputation strategies, in various types of trust/reputation environments. Current work attempts to identify the most viable trust and reputation models stated in the literature, while it further elaborates on the issue by proposing a robust trust and reputation mechanism. This mechanism is incorporated in our agent, HerculAgent, and tested in a variety of environments against the top performing agents of the ART competition. The paper provides a thorough analysis of ART, presents HerculAgent s architecture and dis-cuss its performance.
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