基于兴趣点的电子商务自适应谈判模型

针对电子商务谈判注重良好客户关系的特点,提出基于信息不完备状态下,面向对方兴趣点的自适应谈判模型。定义了谈判双方对谈判项目兴趣点的表示,提出了逐轮淘汰最差权值算法,最后优化出与对方实际权值最相似的权值信息。在此基础上提出基于对方兴趣点的爬山式搜索算法,彻底解决了传统博弈论多属性谈判模型中计算量大而无法实现的问题。实验结果证明,该模型具有良好的对称性、公平性,谈判结果接近Parreto最优。

An Adaptive Negotiation Model Based on Interests to Opposite Side

A model for negotiation was proposed which could self-adapt to interests of opposite side under the incomplete information.The expression of programs of interests to both sides was defined,the most bad weights algorithm of eliminating round after round was proposed,and the weights information was optimized,which was mostly close to the actual weights of the other side.On the basis of this model,a "hill climbing"-search algorithm was put forward to solve negotiation models with multi-attribution based on the traditional game theory field.The experimental results showed this model has good symmetry and fairness.The negotiation results are close to the Parreto-optimality.