| 面向资源分配问题的Q-CF多智能体强化学习 |
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| 引用本文： | 连传强,徐昕,吴军,李兆斌.面向资源分配问题的Q-CF多智能体强化学习[J].智能系统学报,2011,6(2):95-100. |
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| 作者姓名： | 连传强 徐昕 吴军 李兆斌 |
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| 作者单位： | 国防科技大学机电工程与自动化学院,湖南长沙,410073 |
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| 基金项目： | 国家自然科学基金资助项目 |
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| 摘 要： | 多智能体强化学习算法在用于复杂的分布式系统时存在着状态空间大、学习效率低等问题.针对网络环境中的资源分配问题对多智能体强化学习算法进行了研究,将Q-学习算法和链式反馈(chain feedback,CF)学习算法相结合,提出了Q-CF多智能体强化学习算法,利用一种称为信息链式反馈的机制实现了多智能体之间的高效协同.仿真...
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| 关 键 词： | 多智能体系统 强化学习 资源分配 协同控制 |
Q-CF multi-Agent reinforcement learning for resource allocation problems |
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| LIAN Chuanqiang,XU Xin,WU Jun,LI Zhaobin.Q-CF multi-Agent reinforcement learning for resource allocation problems[J].CAAL Transactions on Intelligent Systems,2011,6(2):95-100. |
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| Authors: | LIAN Chuanqiang XU Xin WU Jun LI Zhaobin |
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| Affiliation: | LIAN Chuanqiang,XU Xin,WU Jun,LI Zhaobin(College of Mechatronics and Automation,National University of Defense Technology,Changsha 410073,China) |
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| Abstract: | When a multi-Agent reinforcement learning algorithm is used in complex distributed systems,problems such as huge state space and low learning efficiency arise.In this paper,a multi-Agent reinforcement learning algorithm was studied for the resource allocation problem in a network environment.By combining the Q-learning algorithm and the chain feedback learning mechanism,a novel Q-CF multi-Agent reinforcement learning algorithm was presented.In the Q-CF algorithm,multi-Agent cooperation was realized based on... |
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| Keywords: | multi-Agent system reinforcement learning resource allocation cooperation control |
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