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基于模糊Q-学习的多智能体协作策略研究 被引量：1

Cooperation strategy among multi-agent based on fuzzy Q-learning
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摘要 研究了对机器人足球中的非控球队员同控球队员的协作问题.机器人根据当前状态下机器人和球的位置信息决定目标位置.对目标位置的确定进行了Q学习,对于场地的划分和角色的分配,采用了模糊理论,并对学习结果进行了仿真试验. The cooperation of the non-control robot with the control robot is studied. The destination of the robot is determined by the situation of the robots and ball, which is learned with the Q-learning. The partition of the region and the assignment of the roles are preformed by fuzzy theory. And the simulation experiment is made to verify the result of the learning.
作者 郝宗波 洪炳镕 周彤
机构地区 哈尔滨工业大学计算机科学与技术学院
出处 《哈尔滨工业大学学报》 EI CAS CSCD 北大核心 2004年第7期931-933,共3页 Journal of Harbin Institute of Technology
基金 国家高技术研究发展计划资助项目(863-2001AA422270).
关键词 协作 Q学习 模糊 Computer simulation Fuzzy sets Multi agent systems Robot learning
分类号 TP24 [自动化与计算机技术—检测技术与自动化装置]
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参考文献4

二级参考文献24

  • 1[1]Tucker Balch. Learning Roles: Behavioral Diversity in Robot Teams. In AAAI-97 Workshop on Multiagent Learning.Providence, R.I, 1997
  • 2[2]Christopher J C H Watkins. Technical Note:Q-Learning. Machine Learning, 1992,8: 279-292
  • 3[3]Leslie Pack Kaelbling, Michael L Littman. Reinforcement Learning: A Survey. Journal of Artificial IntelligenceResearch 1996,4: 237-285
  • 4[1]M L Littman. Markov games as framework for multi-agent reinforcement learning[A]. Proc of the 11th Int Conf on Machine Learning[C]. San Francisco: Morgan Kaufmann,1994.157-163.
  • 5[2]J Hu, M P Wellman. Multiagent reinforcement learning: Theoretical framework and an algorithm[A]. Proc of the 15th Int Conf on Machine Learning[C]. Morgan Kaufmann,1998.242-250.
  • 6[3]C Claus, C Boutilier. The dynamics of reinforcement learning in cooperative multiagent systems[A]. Proc of the 15th National Conf on Artificial Intelligence[C]. Cambridge MIT Press,1997.235-262.
  • 7[4]D H Wolpert, K Wheeler, K Tumer, et al. General principles of learning-based multi-agent systems[A]. Proc of the Third Int Conf of Autonomous Agents[C]. Seattle,1999.77-83.
  • 8[5]J A Boyan, M L Littman. Packet routing in dynamically changing networks: A reinforcement learningapproach[J]. Adv in Neur Inform Proc Syst,1993,6:671-678.
  • 9[6]R H Crites, A G Barto. Elevator group control using multiple reinforcement learning agents[J]. Machine Learning,1998,33:235-262.
  • 10[7]J Schneider, W K Wong, A Moore, et al. Distributed value functions[A]. Proc of the 16th Int Conf on Machine Learning[C]. San Francisco: Morgan Kaufmann,1999.371-378.

共引文献43

同被引文献7

  • 1韩伟,王云,王成道,白治江.基于公共知识的电子市场定价算法[J].计算机应用,2005,25(8):1833-1835. 被引量：2
  • 2杜春侠,高云,张文.多智能体系统中具有先验知识的Q学习算法[J].清华大学学报（自然科学版）,2005,45(7):981-984. 被引量：21
  • 3韩伟,陈优广,姜昌华.基于内省推理的多agent在线学习方法[J].模式识别与人工智能,2007,20(2):254-260. 被引量：5
  • 4Hu J, Wellman M P. Muhiagent reinforcement learning: Theoretical framework and algorithm [ C ]//Proceeding of 15th International Conference on Machine Learning. Madison, San Francisco, CA : Morgan Kaufmann Publishers Press, 1998:242 - 250.
  • 5Littman M L. Markov games as a framework for multi-agent reinforcement learning [ C ]//New Brunswick. Proc. 11th international comference on Machine Learning. NJ, Morgan Kaufmann,San. Mateo,1994: 157 - 163.
  • 6Carmel D, Markovitch S. Opponent Modeling in Multi-agent Systems [M/OL]. http://www. cs. technion. ac. il/-shaulm/papers/pdf/ Carmel-Markovitch-Inai1996. pdf.
  • 7Han Wei, Liu Lingbo, Zheng Huaili. Dynamic Pricing by Multiagent Rreinforcement Learning[ C ]//Proceedings of the International Symposium on Electronic Commerce and Security ,2008, Guangzhou, China.

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哈尔滨工业大学学报
2004年 第7期

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