Modeling opponent's beliefs via fuzzy constraint-directed approach in agent negotiation

Authors:
Ting-Jung Yu;K. Robert Lai;Menq-Wen Lin;Bo-Ruei Kao
Affiliations:
Department of Computer Science & Engineering Yuan Ze University, Chung-Li, Taiwan R.O.C.;Department of Computer Science & Engineering Yuan Ze University, Chung-Li, Taiwan R.O.C.;Department of Information Management, Ching Yun University, Chung-Li, Taiwan R.O.C.;Department of Computer Science & Engineering Yuan Ze University, Chung-Li, Taiwan R.O.C.
Venue:
ICIC'07 Proceedings of the intelligent computing 3rd international conference on Advanced intelligent computing theories and applications
Year:
2007

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Abstract

This work adopted the fuzzy constraint-directed approach to model opponent's beliefs in agent negotiation. The fuzzy constraint-directed approach involves the fuzzy probability constraint and the fuzzy instance reasoning. The fuzzy probability constraint is used to cluster the opponent's regularities and to eliminate the noisy hypotheses or beliefs, so as to increase the efficiency on the convergence of behavior patterns and to improve the effectiveness on beliefs learning. The fuzzy instance reasoning reuses the prior opponent knowledge to speed up problem-solving, and reason the proximate regularities to acquire desirable results on predicting opponent behavior. Besides, the proposed interaction method allows the agent to make a concession dynamically based on desirable objectives. Moreover, experimental results suggest that the proposed framework enabled an agent to achieve a higher reward, a fairer deal, or a less cost of negotiation.