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题名: Multiagent reinforcement learning for a planetary exploration multirobot system
作者: Zhang Z(张政) ; Ma SG(马书根) ; Cao BG(曹秉刚) ; Zhang LP(张力平) ; Li B(李斌)
作者部门: 机器人学研究室
会议名称: 9th Pacific Rim International Workshop on Multi-Agents
会议日期: August 7-8, 2006
会议地点: Guilin, China
会议录: AGENT COMPUTING AND MULTI-AGENT SYSTEMS
会议录出版者: SPRINGER-VERLAG
会议录出版地: BERLIN
出版日期: 2006
页码: 339-350
收录类别: SCI ; CPCI(ISTP) ; EI
ISSN号: 0302-9743
ISBN号: 3-540-36707-1
摘要: In a planetary rover system called "SMC rover", the motion coordination between robots is a key problem to be solved. Multiagent reinforcement learning methods for multirobot coordination strategy learning are investigated. A reinforcement learning based coordination mechanism is proposed for the exploration system. Four-robot climbing a slope is studied in detail as an instance. The actions of the robots are divided into two layers and realized respectively, which simplified the complexity of the climbing task. A Q-Learning based multirobot coordination strategy mechanism is proposed for the climbing mission. An OpenGL 3D simulation platform is used to verify the strategy and the learning results.
语种: 英语
产权排序: 1
WOS记录号: WOS:000239626100033
Citation statistics:
内容类型: 会议论文
URI标识: http://ir.sia.cn/handle/173321/8794
Appears in Collections:机器人学研究室_会议论文

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Recommended Citation:
张政;马书根; 曹秉刚; 张力平; 李斌.Multiagent reinforcement learning for a planetary exploration multirobot system.见:SPRINGER-VERLAG.AGENT COMPUTING AND MULTI-AGENT SYSTEMS,BERLIN,2006,339-350
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