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	MAS-Soccer: a testbed based on multi-agent cooperation
	Zhang Shuangmin ; Shi Chunyi
	2010-05-06 ; 2010-05-06
关键词	Practical/ feature extraction learning (artificial intelligence) mobile robots multi-agent systems multi-robot systems/ MAS-Soccer multi-agent cooperation reinforcement learning algorithms feature vector extraction Q-learning algorithm Robocup/ C3390C Mobile robots C6170K Knowledge engineering techniques
中文摘要	A testbed is needed to test and compare various multi-agent cooperative problem solving algorithms. A multi-agent cooperative simulation system based on BDI reasoning, MAS-Soccer, was developed to emphasize the importance of joint strategies in multi-agent systems, rather than the performance details of specific actions. The system can be used to test reinforcement learning algorithms based on feature vector extraction and the traditional Q-learning algorithm in the Robocup free kick game. Tests illustrate the efficiency of the system and that MAS-Soccer can efficiently and correctly compare various cooperative strategies.
语种	英语 ; 英语
出版者	Tsinghua Univ. Press ; China
内容类型	期刊论文
源URL	[http://hdl.handle.net/123456789/10060]
专题	清华大学
推荐引用方式 GB/T 7714	Zhang Shuangmin,Shi Chunyi. MAS-Soccer: a testbed based on multi-agent cooperation[J],2010, 2010.
APA	Zhang Shuangmin,&Shi Chunyi.(2010).MAS-Soccer: a testbed based on multi-agent cooperation..
MLA	Zhang Shuangmin,et al."MAS-Soccer: a testbed based on multi-agent cooperation".(2010).

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