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We study finite-state, finite-action, discounted infinite-horizon Markov decision processes with uncertain correlated transition matrices in deterministic policy spaces. Existing robust dynamic programming methods cannot be extended to solving this class of general problems. In this paper, based on a robust optimality criterion, an approximate robust policy iteration using a multilayer perceptron...
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