年次大会講演論文集
Online ISSN : 2433-1325
会議情報
3120 連続環境における移動ロボットの強化学習
川田 誠一谷村 暁之小口 俊樹
著者情報
会議録・要旨集 フリー

p. 239-240

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抄録
In this paper, New Reinforcement Learning based Path-Planning task is proposed for mobile robot system. The proposed algorithms are based upon the k-certainty exploration method and the k-certainty exploration method with PIA to be used for continuous environment. Experimental results show that the k-certainty exploration method and the k-certainty exploration method with PIA for continuous environment are more effective than the conventional Q-learning.
著者関連情報
© 2003 一般社団法人日本機械学会
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