| 基于贝叶斯分类的增强学习协商策略 |
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| 引用本文： | 孙天昊,陈飞,朱庆生,曹峰.基于贝叶斯分类的增强学习协商策略[J].计算机科学,2011,38(9):227-229. |
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| 作者姓名： | 孙天昊 陈飞 朱庆生 曹峰 |
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| 作者单位： | (重庆大学计算机学院 重庆 400030)；(中国嘉陵工业股份有限公司(集团)信息技术部 重庆 400032} |
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| 基金项目： | 本文受中央高校基本科研业务费科研专项项目(CDJRClO180012,CDJZR1Ol80014)资助 |
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| 摘 要： | 为了帮助协商Agent选择最优行动实现其最终目标，提出基于贝叶斯分类的增强学习协商策略。在协商过程中，协商Agent根据对手历史信息，利用贝叶斯分类确定对手类型，并及时动态地调整协商Agent对对手的信念。协商Agen、通过不断修正对对手的信念，来加快协商解的收敛并获得更优的协商解。最后通过实验验证了策略的有效性和可用性。
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| 关 键 词： | 贝叶斯分类，增强学习，协商策略，协商历史 |
Reinforcement Learning Negotiation Strategy Based on Bayesian Classification |
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| SUN I}ian-hao,CHEN Fei,ZHU Qing-sheng,CAO Feng.Reinforcement Learning Negotiation Strategy Based on Bayesian Classification[J].Computer Science,2011,38(9):227-229. |
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| Authors: | SUN I}ian-hao CHEN Fei ZHU Qing-sheng CAO Feng |
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| Affiliation: | SUN Tian-hao1,2 CHEN Fei1 ZHU Qing-sheng1 CAO Feng2 (College of Computer Science,Chongqing University,Chongqing 400030,China)1(Department of Information Technology,China Jialing Industrial Co.,Ltd(Group),Chongqing 400032,China)2 |
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| Abstract: | 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 |
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| Keywords: | Bayesian classification Reinforcement learning Negotiation strategy Negotiation history |
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