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In this work, we propose a new fuzzy reinforcement learning algorithm for differential games that have continuous state and action spaces. The proposed algorithm uses function approximation systems whose parameters are updated differently from the updating mechanisms used in the algorithms proposed in the literature. Unlike the algorithms presented in the literature which use the direct algorithms...
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