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Faster saddle-point optimization for solving large-scale Markov decision processes

By Joan Bas-Serrano and Gergely Neu at
LogoUniversitat Pompeu Fabra
We consider the problem of computing optimal policies in average-reward Markov decision processes. This classical problem can be formulated as a linear program directly amenable to saddle-point optimization methods, albeit with a number of variables that is linear in the number of states. To address this issue, recent work has... Show more
January 10, 2020
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Faster saddle-point optimization for solving large-scale Markov decision processes
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