Emotion Behavior Learning System Based on Target Selection-Type Q-Learning with Dynamic Learning Parameters Tuned by Neuromodulators

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  • AKIGUCHI Shunsuke
    Department of System Design Engineering, Graduate School of Engineering, University of Fukui
  • MAEDA Yoichiro
    Dept. of Human and Artificial Intelligent Systems, Graduate School of Engineering, University of Fukui

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  • 神経修飾物質系による動的学習パラメータを有する目標選択型Q-Learningに基づく情動行動学習システム
  • シンケイ シュウショク ブッシツケイ ニ ヨル ドウテキ ガクシュウ パラメータ オ ユウスル モクヒョウ センタクガタ Q Learning ニ モトズク ジョウドウ コウドウ ガクシュウ システム

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In recent years, in the field of the entertainment robot and nursing care robot, several methods for embedding human emotions to the robot have been developed actively. In this paper, in order to realize emotion generating and emotion behavior more appropriate for a living thing, we embed to a robot about the model of neuromodulators that exists in human's brain and propose the learning method of the emotion behavior using Q-Learning that has meta-parameter control. In this method, we propose a target selection-type Q-Learning method with plural Q-values concerning the maximization and minimization of rewards and punishments. We aim at the realization of a system to obtain complicated emotion behaviors selected based on the positive and negative evaluation according to the situation. Furthermore, we also report the result of an experiment by computer simulation and Kansei evaluation to confirm the efficiency of proposed method.

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