ロボティクス・メカトロニクス講演会講演概要集
Online ISSN : 2424-3124
セッションID: 2A1-M05
会議情報
2A1-M05 強化学習における報酬情報に基づいた学習率の制御法(進化・学習とロボティクス)
鎌田 徹平中澤 和夫
著者情報
会議録・要旨集 フリー

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抄録
Recently, as robotics has been developed, it is expected that robots are workforce taking place of people. Conventionally, rules for controlling the robots are designed by a designer, but under unknown environment with various uncertainties, it is difficult to design the rules previously. Therefore, there are many researches on controlling autonomous robots with learning abilities, especially reinforcement learning attracts attention. Reinforcement learning largely depends on parameters. Accordingly, it is necessary to develop an algorithm which can set parameters autonomously according to the state of the environment and the advance condition of learning while learning. In this research, it aims at developing a new algorithm controlling the parameters based on only reward information while learning.
著者関連情報
© 2007 一般社団法人 日本機械学会
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