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A Novel Clustering Method Curbing the Number of States in Reinforcement Learning
強化学習における状態数を抑制するクラスタリング方法
2009
Transactions of the Institute of Systems Control and Information Engineers
強化学習における状態数を抑制するクラスタリング方法
We propose an efficient state-space construction method for a reinforcement learning. Our method controls the number of categories with improving the clustering method of Fuzzy ART which is an autonomous state-space construction method. The proposed method represents weight vector as the mean value of input vectors in order to curb the number of new categories and eliminates categories whose state values are low to curb the total number of categories. As the state value is updated, the size of
doi:10.5687/iscie.22.21
fatcat:ngcg5jxvhnfv3egyyikg7jrezm