A New Learning Algorithm for the Hierarchical Structure Learning Automata Operating in the General Multiteacher Environment(Automata and Formal Language Theory)
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概要
- 論文の詳細を見る
Learning behaviors of hierarchically structured stochastic automata operating in a general nonstationary multiteacher environment are considered. It is shown that convergence with probability 1 to the optimal path is ensured by a new learning algorithm which is an extended form of the relative reward strength algorithm. Several computer simulation results confirm the effectiveness of the proposed algorithm.
- 社団法人電子情報通信学会の論文
- 2004-05-01
著者
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Mogami Y
Department Of Biology Ochanomizu University
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Baba N
Department Of Applied Physics Hokkaido University
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Baba Norio
Department Of Information Science Osaka Kyoiku Univ.
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Baba Norio
Department Of Electrical Engineering Kogakuin University
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Mogami Yoshio
Department Of Information Science And Intelligent Systems Faculty Of Engineering University Of Tokus
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