Buying and selling with insurance in open multi-agent marketplace
PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
Towards modeling trust based decisions: a game theoretic approach
ESORICS'07 Proceedings of the 12th European conference on Research in Computer Security
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In this paper, we propose buying and selling models for agents to trade in the open multi-agent marketplace. Unlike auctions, we take into account of the fact that agents trading in such open environments has to maximize their profits and at the same time, protect themselves from fraud and deception. We attempt to address this issue by incorporating the element of trust and risk management into our proposed buying and selling model. During buying, agents learn to select their partners based on the trustworthiness of the potential partner as well as its personal risk attitude. During selling, agents learn to increase the chances of winning a deal by adjusting their profit rate, which is a measure that considers both trust and risk. The novelty of this proposal is that it ensures agents continuing to seek maximum expected utility in a dynamic trading environment. Our experimental results confirm the feasibility of our approach.