A Guided Genetic Algorithm for Bilateral Negotiation with Incomplete Information

Abstract:

Reaching an agreement between negotiators is a complex process. The complexity of the problem is depicted by the difference preference of negotiators, the size of the solution space and the negotiation procedure. The aim of this study is to develop an automated negotiation method using a genetic algorithm as a mechanism. The proposed method uses theestimation of the zone of agreementtoguide negotiation. Time and joint utility are used as performance indicators. The result shows that the proposed method hasa better time usage than others.However, our method could have poor value of joint utility in some cases. A likely explanation is that the progress rate of the negotiators affects the joint payoff.

• Periodical: Advanced Materials Research (Volumes 931-932)
• Pages: 1422-1426
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.931-932.1422
• Online since: May 2014
• Authors: Teerapat Threepatcharatip*, Samerkae Somhom
• Keywords: Genetic Algorithm (GA), Negotiation Problem, Opponents Preference Estimation

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