Multi-Robot Cooperation Strategy in Game Environment Using Deep Reinforcement Learning

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	Multi-Robot Cooperation Strategy in Game Environment Using Deep Reinforcement Learning
	He YQ(何玉庆)1,3 ; Zhang HD(张宏达)1,2,3; Li DC(李德才)1,3
	2018
会议日期	December 12-15, 2018
会议地点	Kuala Lumpur, Malaysia
页码	886-891
英文摘要	The multi-robot system combines the characteristics and advantages of each component robot and can break through the constraints of a single robot capability, greatly expanding the application of the robot. However, in the game environment, multi-robot systems face the challenge of intelligent decision-making in high-dimensional complex dynamic environments. The research progress of multi-agent decision-making strategies in the game environment based on deep reinforcement learning provides a solution for solving the problems faced by multi-robot systems. To this end, based on the deep reinforcement learning method, we analyze the multi-agent collaboration strategy in the game environment and propose a learning method that can measure cooperative information between multiple agents. On this basis, we conduct a Nash equilibrium game strategy analysis on the specific multi-agent game problem--the territory defense, use deep Q learning method to learn the defender's joint defense strategy. We conducted simulation experiments and verified the effectiveness of our method. Furthermore, we conducted experiments on the actual multi-robot system platform and demonstrated the feasibility of multi-agent cooperation strategy in practical multi-robot system based on deep reinforcement learning.
产权排序	1
会议录	Proceedings of the 2018 IEEE International Conference on Robotics and Biomimetics (IEEE ROBIO 2018)
会议录出版者	IEEE
会议录出版地	New York
语种	英语
ISBN号	978-1-7281-0376-1
内容类型	会议论文
源URL	[http://ir.sia.cn/handle/173321/23863]
专题	沈阳自动化研究所_机器人学研究室
通讯作者	Zhang HD(张宏达)
作者单位	1.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016 2.University of Chinese Academy of Sciences, Beijing 100049, China 3.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110016
推荐引用方式 GB/T 7714	He YQ,Zhang HD,Li DC. Multi-Robot Cooperation Strategy in Game Environment Using Deep Reinforcement Learning[C]. 见:. Kuala Lumpur, Malaysia. December 12-15, 2018.