Jianlin Qiu

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In reinforcement learning problems with large-scale and continuous state or action spaces, the approximate reinforcement learning methods are proposed by using function approximation methods to fit the policy. The least-square approximation can extract more useful information from the samples and can be applied to the online algorithms effectively. Because(More)