| 基于强化学习的多机器人避碰算法研究 |
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| 引用本文： | 段勇,陈腾峰. 基于强化学习的多机器人避碰算法研究[J]. 信息技术, 2012, 0(6): 100-103 |
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| 作者姓名： | 段勇 陈腾峰 |
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| 作者单位： | 沈阳工业大学信息科学与工程学院,沈阳,110870 |
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| 摘 要： | 采用强化学习解决多机器人避碰问题。然后针对表格式Q学习算法只能用于离散的状态并且学习时间过长,难以收敛的不足,提出了神经网络和Q学习相结合的算法。最后将该算法应用到多机器人避碰问题中,仿真实验表明该算法有效,能较好地解决多机器人避碰问题。
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| 关 键 词： | 多机器人避碰 强化学习 神经网络 |
Algorithm of multi-robot collision avoidance based on reinforcement learning |
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| DUAN Yong , CHEN Teng-feng. Algorithm of multi-robot collision avoidance based on reinforcement learning[J]. Information Technology, 2012, 0(6): 100-103 |
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| Authors: | DUAN Yong CHEN Teng-feng |
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| Affiliation: | (School of Information Science and Engineering,Shenyang University of Technology,Shenyang 110870,China) |
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| Abstract: | This paper adopts reinforcement learning to solve multi-robot collision avoidance problems.Then in allusion to the insufficiency that tabular Q-learning algorithm can only be used for discrete states and learning time is too long,difficult to convergence,it puts forward combination of neural networks and Q-learning algorithms.Finally the algorithm is applied to multi-robot collision avoidance problems.The simulation experiments show that the algorithm is effective and well solve the multi-robot collision avoidance problems. |
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| Keywords: | multi-robot collision avoidance reinforcement learning neural networks |
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