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- W2119031567 abstract "A self-organizing control mechanism with a capability of reinforcement learning is proposed. The method is realized by a reinforcement signal predictor based on the grey theory and a policy learning unit implemented by a neural network. In consideration of the stability problem in learning, temporal difference algorithm is used as the weight-update rule of the connectionist From the results of the simulations and experiments, the proposed method demonstrates that a control task can be learned even with very little a priori knowledge." @default.
- W2119031567 created "2016-06-24" @default.
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- W2119031567 date "2007-03-01" @default.
- W2119031567 modified "2023-09-26" @default.
- W2119031567 title "A Grey Approximation Approach to State Value Function in Reinforcement Learning" @default.
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- W2119031567 doi "https://doi.org/10.1109/icitechnology.2007.4290500" @default.
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