协商Agent的历史学习算法研究

Agent's Learning Algorithm Research on the Negotiation History

文章以买方Agent的观点对交易平台上获得的对方Agent历史协商信息进行分析,并根据其特点做初步过滤。在此基础上,该文针对现有协商模型中存在的问题,提出了一个Agent协商历史学习算法,并实验说明了其可行性。该算法可用于Agent协商前初始信念的创建,对Agent在协商中策略的选择、执行具有指导作用。

This paper states the algorithm from the respective of the buyer agent.The negotiation history of the opponent agent is analyzed firstly,which is obtained from the trade platform.Then it is pre-filtered on the characteristic of data structures.On the basis of the above,it proposes a learning algorithm on the agent negotiation history after analyzing the problems of the present negotiation models.This algorithm can be used to update of the initial beliefs of the agent before negotiation,and plays a guidable role in selecting and implementing the tactics in agent negotiation.