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State space construction for cooperative behavior acquisition in the environments including multiple learning robots

机译:包含多个学习机器人的环境中用于协作行为获取的状态空间构建

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摘要

This paper proposes a method that acquires cooperative behaviors based on the estimation of the state vectors. In order to acquire the cooperative behaviors in multi robots environments, each learning robot estimates the local predictive model between the learner and the other objects separately. Based on the local predictive models, robots learn the desired behaviors using reinforcement learning. The proposed method is applied to a soccer playing situation, where a rolling ball and other moving robots are well modeled and the learner's behaviors are successfully acquired by the method. Computer simulations and real experiments are shown and a discussion is given.
机译:本文提出了一种基于状态向量估计的合作行为获取方法。为了获得多机器人环境中的协作行为,每个学习机器人分别估计学习者和其他对象之间的局部预测模型。机器人基于局部预测模型,通过强化学习来学习所需的行为。所提出的方法适用于足球比赛的情况,其中对滚球和其他移动机器人进行了很好的建模,并且该方法成功地获取了学习者的行为。显示了计算机模拟和实际实验,并进行了讨论。

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