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Reinforcement learning (RL) is a model-free framework for solving optimal control problems stated as Markov decision processes (MDPs) (Puterman, 1994). MDPs work in discrete time: at each time step, the controller receives feedback from the system in the form of a state signal, and takes an action in response.
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