| 引用本文: | 仲 宇, 顾国昌, 张汝波.多智能体系统中的分布式强化学习研究现状[J].控制理论与应用,2003,20(3):317~322.[点击复制] |
| ZHONG Yu, GU Guo-chang, ZHANG Ru-bo.Survey of distributed reinforcement learning algorithms in multi-agent systems[J].Control Theory and Technology,2003,20(3):317~322.[点击复制] |
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| 多智能体系统中的分布式强化学习研究现状 |
| Survey of distributed reinforcement learning algorithms in multi-agent systems |
| 摘要点击 5227 全文点击 5194 投稿时间：2001-11-13 修订日期：2002-11-20 |
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| DOI编号 10.7641/j.issn.1000-8152.2003.3.001 |
| 2003,20(3):317-322 |
| 中文关键词 分布式强化学习 多智能体系统 机器学习 |
| 英文关键词 distributed reinforcement learning multi-agent system machine learning |
| 基金项目 中国科学院机器人学开放研究实验室基金(RL2000106); 某国防基础研究基金. |
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| 中文摘要 |
| 对目前世界上分布式强化学习方法的研究成果加以总结, 分析比较了独立强化学习、社会强化学习和群体强化学习三类分布式强化学习方法的特点、差别和适用范围, 并对分布式强化学习仍需解决的问题和未来的发展方向进行了探讨. |
| 英文摘要 |
| The achievements in distributed reinforcement learning algorithms are introduced. The present distributed reinforcement learning algorithms are classified into three categories, and the characteristics and application ranges of three classes of distributed reinforcement learning algorithms are compared. At the end of the article, the problems to be solved and the futher works are discussed. |