Our research is within the area of artifificial intelligence and multi-agent systems. More specififically, we focus on evaluating trust relationships between the agents in multi-agent e-marketplaces and sensor networks and aim to address the following problems, • how to identify a trustworthy (good quality) agent • how to cope with dishonest advisors i.e., agents who provide misleading opinions about others To explain, in multi-agent e-marketplaces, self-interested selling agents may act maliciously by not delivering products with the same quality as promised. It is thus important for buying agents to analyze their quality and determine which sellers to do business with, based on their previous experience with the sellers. However, in most e-markets, buyers often encounter sellers with which they have no previous experience. In such cases, they can query other buyers (called advisors) about the sellers. But, advisors may act dishonestly by providing misleading opinions (unfair ratings) to promote low quality sellers or demote sellers with high quality [Irissappane et al., 2014a]. Hence, it is necessary to evaluate the quality of advisors’ opinions to determine their reliability