Optimized negotiation strategy based on reinforcement learning

doi:10.3778/j.issn.1002-8331.2008.30.007

Computer Engineering and Applications ›› 2008, Vol. 44 ›› Issue (30): 24-25.DOI: 10.3778/j.issn.1002-8331.2008.30.007

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Optimized negotiation strategy based on reinforcement learning

SUN Tian-hao,ZHU Qing-sheng,LI Shuang-qing,ZHOU Ming-qiang

College of Computer，Chongqing University，Chongqing 400030，China

Received:2008-07-01 Revised:2008-07-28 Online:2008-10-21 Published:2008-10-21
Contact: SUN Tian-hao

一种优化的基于增强学习协商策略

孙天昊,朱庆生,李双庆,周明强

重庆大学计算机学院，重庆 400030

通讯作者: 孙天昊

Abstract

Abstract: Negotiation agent can use reinforcement learning to select its best actions and reach its final goal.This paper proposes an optimized negotiation strategy based on reinforcement learning.In the middle of negotiation process，it makes the best use of the opponent’s negotiation history，in order to quicken the negotiation result convergence and enhance the negotiation result quality.Finally，the algorithm is proved to be effective and practical by experiment.

Key words: reinforcement learning, negotiation strategy, negotiation history

摘要： 增强学习可以帮助协商Agent选择最优行动实现其最终目标。对基于增强学习的协商策略进行优化，在协商过程中充分利用对手的历史信息，加快协商解的收敛和提高协商解的质量。最后通过实验验证了算法的有效性和可用性。

关键词: 增强学习, 协商策略, 协商历史

SUN Tian-hao,ZHU Qing-sheng,LI Shuang-qing,ZHOU Ming-qiang. Optimized negotiation strategy based on reinforcement learning[J]. Computer Engineering and Applications, 2008, 44(30): 24-25.

孙天昊,朱庆生,李双庆,周明强. 一种优化的基于增强学习协商策略[J]. 计算机工程与应用, 2008, 44(30): 24-25.

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Optimized negotiation strategy based on reinforcement learning

一种优化的基于增强学习协商策略

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