Automated Negotiation Decision Model Based on Classifier Fusion

Abstract

Abstract: Due to the confidentiality of information in e-commerce environment, negotiation participants can not get opponent’s negotiation preferences, thereby affecting the negotiation performance. To solve this, an automated negotiation decision model based on classifier fusion was proposed. The model incorporates support vector machine and Bayesian classifier by combining the advantages of both, improving the effect of classification learning of negotiation preferences. Based on accurate estimation of opponent’s negotiation preference, a particle swarm optimization algorithm was used to search the optimal counter proposal. The experimental data show that the new method is better than the single classifier, and can maintain a high total negotiation utility in the noisy small scale training set.

Key words: automated negotiation, support vector machine, Bayesian

CLC Number:

TP 18

PENG Yan-Bin-1, ZHENG Zhi-Jun-1, YU Cheng-Bo-2, LI Ji-Ming-3. Automated Negotiation Decision Model Based on Classifier Fusion[J]. Journal of Shanghai Jiaotong University, 2013, 47(04): 644-649.

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