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基于最先策略增强学习的ART2神经网络*

, PP. 428-432

Keywords: 增强学习,ART2神经网络,最先策略,避碰撞

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Abstract:

提出一种基于最先策略增强学习的ART2神经网络FPRLART2(ForemostPolicyReinforcementLearningbasedART2neuralnetwork),并介绍其学习算法.为了达到在线学习的目的,在FPRLART2中,从状态到行为值之间的映射中,选择第一个得到奖励的行为,而不是选择诸如1stepQLearning中具有最优行为值的行为.ART2神经网络用于存储分类模式,其权重通过增强学习增强或减弱,达到学习的目的.并将FPRLART2运用到移动机器人避碰撞问题的研究中.仿真实验表明,引入FPRLART2后减少移动机器人与障碍物发生碰撞的次数,具有良好的避碰效果.

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