| 基于模糊推理的多智能体强化学习 |
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| 引用本文： | 韩伟,鲁霜.基于模糊推理的多智能体强化学习[J].计算机应用与软件,2011,28(11):96-98,107. |
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| 作者姓名： | 韩伟 鲁霜 |
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| 作者单位： | 南京财经大学信息工程学院 江苏南京210046 |
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| 基金项目： | 国家自然科学基金项目(70802025) |
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| 摘 要： | 以电子市场智能定价问题为研究背景,提出基于模糊推理的多智能体强化学习算法(FI-MARL).在马尔科夫博弈学习框架下,将领域知识初始化为一个模糊规则集合,智能体基于模糊规则选择动作,并采用强化学习来强化模糊规则.该方法有效融合应用背景的领域知识,充分利用样本信息并降低学习空间维数,从而增强在线学习性能.在电子市场定价的...
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| 关 键 词： | 强化学习(RL) 多智能体系统(MAS) 模糊推理 电子市场 |
FUZZY INFERENCE BASED MULTI-AGENT REINFORCEMENT LEARNING |
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| Han Wei,Lu Shuang.FUZZY INFERENCE BASED MULTI-AGENT REINFORCEMENT LEARNING[J].Computer Applications and Software,2011,28(11):96-98,107. |
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| Authors: | Han Wei Lu Shuang |
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| Affiliation: | Han Wei Lu Shuang (School of Information Engineering,Nanjing University of Finance and Economics,Nanjing 210046,Jiangsu,China) |
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| Abstract: | Under the background of pricing in electronic markets,a multi-agent reinforcement learning algorithm based on fuzzy inference is proposed.Within Markov stochastic game framework,domain knowledge is initialized into fuzzy rules.Agents choose their actions according to those rules,which are updated by reinforcement learning.By doing so,Domain knowledge is effectively integrated;each domain sample is effectively exploited;more importantly,the learning dimension is greatly reduced.Compassion with former pricing... |
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| Keywords: | Reinforcement learning(RL) Multi-agent system(MAS) Fuzzy inference Electronic market |
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