%0 Journal Article
%T Reinforcement Learning Negotiation Strategy Based on Bayesian Classification<br>基于贝叶斯分类的增强学习协商策略
%A SUN I}ian-hao
%A CHEN Fei
%A ZHU Qing-sheng
%A CAO Feng
%A <br>孙天昊
%A 陈飞
%A 朱庆生
%A 曹峰
%J 计算机科学
%D 2011
%I 
%X To help negotiation Agent to select its best actions and reach its final goal,a reinforcement learning ncgotialion strategy based on I3ayesian classification was proposed. In the middle of negotiation process, negotiation Agent makes the best use of the opponent's negotiation history to make a decision of the opponent's type based on Bayesian classification,dynamically adjust the negotiation Agent's belief of opponent in time,quicken the negotiation result convergence and reach the better negotiation result. Finally, the algorithm was proved to be effective and practical by experiment
%K Bayesian classification
%K Reinforcement learning
%K Negotiation strategy
%K Negotiation history<br>贝叶斯分类，增强学习，协商策略，协商历史
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=A72829DDE955E0D2C454E25C179ECA84&yid=9377ED8094509821&vid=16D8618C6164A3ED&iid=9CF7A0430CBB2DFD&sid=0DEB7A8A66C33AAD&eid=F8035C8B7D8A4264&journal_id=1002-137X&journal_name=计算机科学&referenced_num=0&reference_num=0