Agent Trust Management Based on Human Plausible Reasoning: Application to Web Search

Abstract

In open systems, different service providers can join and leave at any time. Multi Agent Systems (MASs) are being used more and more as the basis of open systems. Although openness brings a huge opportunity for different systems to operate in a decoupled and autonomous manner, it can introduce untrustworthy agents into the society. For this purpose, Agent Trust Management (ATM) methods have been proposed to try to eliminate this defect. This paper presents a general framework for managing trust in MASs based on the theory of Human Plausible Reasoning (HPR). The goal of the proposed framework is to determine for each user a ranked list of trusted agents and to find newer possible trust relationships between users and agents. We use the HPR certainty parameters to define how trustworthy each agent is in the list. We measure the agent trust according to two metrics: the direct interaction rating and third-party references. For each user, a third party is any other user with whom a HPR relationship exists. We aggregate the direct interaction rating value and the reputation values of third parties to achieve a single quantitative value for the trust. This value is then used to rank the agents. We apply our HPR-based ATM framework to the domain of Web search. The resulting ATM system provides the user a list of trusted search engines ranked according to the reputation the search engine has gained by interacting with other related users as well as the retrieval precision of pages returned in response to the user's query.