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Decision making based on reinforcement learning and emotion learning for social behavior

Atsushi Matsuda, Hideaki Misawa, Keiichi Horio

发表年份
2011
引用次数
10

摘要

In this paper, we propose a decision making method based on reinforcement learning and emotion learning (DRE) for inducing social behaviors of robots. Emotion of animals has an important role in their social interactions. We attempt to incorporate emotion into decision making of robots. To make a social decision making, the DRE combines a decision based on intrinsic fear emotion with a strategic decision obtained by reinforcement learning. Agents with the DRE learn state values by reinforcement learning and learn emotion values by fear emotion learning. In simulation experiments, the effectiveness of the DRE is verified concerning the emergence of social behaviors and the adaptability to an environmental change through an unmoving target search problem.

关键词

Reinforcement learningAdaptabilityReinforcementSocial decision makingComputer sciencePsychologyRobotSocial learningError-driven learningArtificial intelligence

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