Adaptive Multi-Issue Agent-Based Negotiation Model

摘要：

This paper presents an adaptive agent-based negotiation model to improve the low efficiency caused by the incomplete information and the diversity of backgrounds of the negotiating parties. Our model at first utilizes the Market-Driver Model to make adjustable rates of overall concession, and then learns opponent’s preference using Bayesian learning, at last takes account of the factors affecting the negotiation process (the issue’s weight, the similarity degree of the two sides’ bid, and the available concession range) and allocates the overall concession to each issue appropriately. This model helps maximum the benefit of both sides, improves the efficiency of negotiation. Our experiments show that this model has better adaptability to the changing situation of the environment and the negotiation process. Especially when the preferences of the two sides are quite different, our model can get a better result and create a win-win situation.

关键词： Automated negotiation Intelligent agents Multi-issue Bayesian learning Market-Driven Model

作者: Chun Shen Xiuzeng Peng Yi Lu Lei Liu

作者单位: College of Computer Science and Technology,Jilin University Changchun 130012,China

会议类型: 国际会议

会议名称: 2010 IEEE信息与自动化国际会议(ICIA 2010)

会议地点: 哈尔滨

会议语种:英文

页码: 1-5

在线出版日期: 2010-06-20（万方平台首次上网日期，不代表论文的发表时间）