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Reinforcement Learning: Stochastic Approximation Algorithms for Markov Decision Processes

Published 23 Dec 2015 in math.OC | (1512.07669v1)

Abstract: This article presents a short and concise description of stochastic approximation algorithms in reinforcement learning of Markov decision processes. The algorithms can also be used as a suboptimal method for partially observed Markov decision processes.

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