A framework of fuzzy constraint-directed agent negotiation with learning element

This paper presents a framework of fuzzy constraint- directed agent negotiation with learning element to improve the quality of negotiation. The learning element involves: 1) fuzzy probability constraint for regularizing the opponent´s behavior to decrease the noisy beliefs about the opponent, 2) instance matching method for reusing the prior opponent knowledge to infer the similar feasible actions from similar situations, and 3) the proposed adaptive interaction for specifying the appropriate tradeoff among feasible proposals to reach an agent´s local or global goal.