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A systematic model of stable multilateral automated negotiation in e-market environment

Taiguang Gao,Min Huang,Qing Wang,Mingqiang Yin,W. Ching,L. Lee,Xingwei Wang

Published 2018 in Engineering applications of artificial intelligence

ABSTRACT

Abstract In e-market environment, the participants are usually bilateral such as in Consumer-to-Business or Customer-to-Customer business models. The participant on each side prefers the counterpart from which the concerned issues or profits can be pursued. Hence, the effective matching from a global point of view and the stable matching from an individual point of view become the critical function of the business models. In this paper, a systematic model of Stable Multilateral Automated Negotiation (SMAN) is proposed to facilitate the involved parties’ matching process in two-sided e-market, where confidential mediator agent as well as party agents communicate and make decisions on behalf of their principal parties. To make the matching effective and stable, two optimization models are designed. One is matching points model which makes an effective balance among the proposal value of issues for each possible pair of matching, such that the joint weighted profit measure is optimized with feature rescaling. The other one is matching scheme model which optimizes Social Welfare (SW) subject to the stable constraints, and ensures the engaged individual party satisfies the matching result from its viewpoint. And the optimality of stable matching is proved by mathematical deduction. Finally, numerical experiments are illustrated and show that the designed systematic models can generate effective matchings with individually stable advantages over the traditional Multilateral Automated Negotiation of Two Sides (MANTS).

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