文章基本信息

标题：An Improved Reinforcement Learning Algorithm for Cooperative Behaviors of Mobile Robots
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作者：Yong Song ; Yibin Li ; Xiaoli Wang 等
期刊名称：Journal of Control Science and Engineering
印刷版ISSN：1687-5249
电子版ISSN：1687-5257
出版年度：2014
卷号：2014
DOI：10.1155/2014/270548
出版社：Hindawi Publishing Corporation
摘要：Reinforcement learning algorithm for multirobot will become very slow when the number of robots is increasing resulting in an exponential increase of state space. A sequential Q-learning based on knowledge sharing is presented. The rule repository of robots behaviors is firstly initialized in the process of reinforcement learning. Mobile robots obtain present environmental state by sensors. Then the state will be matched to determine if the relevant behavior rule has been stored in the database. If the rule is present, an action will be chosen in accordance with the knowledge and the rules, and the matching weight will be refined. Otherwise the new rule will be appended to the database. The robots learn according to a given sequence and share the behavior database. We examine the algorithm by multirobot following-surrounding behavior, and find that the improved algorithm can effectively accelerate the convergence speed.