Dotan Di Castro

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In adaptive control, agents interacting with Markov Decision Processes typically face two types of setups. In the first setup, the environment's model is known and dynamic programming and related methods are used to obtain the optimal control. In the second setup, the environment's model is unknown and reinforcement learning methods are used. In this work(More)
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