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Reinforcement structure/parameter learning for neural-network-based fuzzy logic control systems

IEEE T. Fuzzy Systems, no. 1 (1994): 46-63

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This paper proposes a reinforcement neural-network-based fuzzy logic control system (RNN-FLCS) for solving various reinforcement learning problems. The proposed RNN-FLCS is constructed by integrating two neural-network-based fuzzy logic controllers (NN-FLC's), each of which is a connectionist model with a feedforward multilayered network ...更多

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