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Reinforcement learning algorithms for MDPs

By Csaba Szepesvári


Reinforcement learning is a learning paradigm concerned with learning to control a system so as to maximize a numerical performance measure that expresses a long-term objective. The goal in reinforcement learning is to develop efficient learning algorithms, as well as to understand the algorithms ’ merits and limitations. In this article we focus on a few selected algorithms of reinforcement learning which build on the powerful theory of dynamic programming

Topics: reinforcement learning, Markov Decision Processes
Year: 2009
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