A survey unifying the operator-theoretic, probabilistic, and optimization-based mathematical structures underlying modern reinforcement learning algorithms.
An upper bound on the loss from approximate optimal-value functions.Machine Learning, 16(3):227–233, 1994
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Mathematical methods of reinforcement learning
A survey unifying the operator-theoretic, probabilistic, and optimization-based mathematical structures underlying modern reinforcement learning algorithms.