Trust and social networking of multiagent peers

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In this research, we explore four fundamental challenges to modeling trust in multiagent systems -- systems of co-existing intelligent software agents that are designed to problem solve on behalf of their human users -- when making use of advice provided by other agents. The first is to be able to identify and address collusive behaviour among agents (where groups of agents collectively aim to provide deceptive information) for example for e-commerce applications. The second is to set the conditions for delimiting the social network of advising agents, in order to operate with an appropriate number of peers and with peers that have a greater likelihood of being able to provide information of value. The third is to project models of agent trust into two very topical but critical applications with challenges of dynamic change: that of transportation (vehicular agents sharing information to assist in the management of urban traffic) and healthcare (leveraging a social network of trusted peers to provide information to educate a user about a current medical problem). The final project will look more closely at context-specific trust modeling, suggesting that the makeup of the multiagent system (altruistic or malicious agents) and the proclivity of the user (risk averse or risk seeking) will set differing demands for the trust modeling of other agents. In all, this research aims to enable improved decision making by intelligent agents in multiagent environments through novel techniques for reasoning about the other agents that co-exist. With our extensions to address these critical scenarios what will emerge is a methodology for trust modeling that has a significant reach of applicability. In addition, an appreciation for effective delimiting of social networks will emerge.