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Language: en
Pages: 213
Pages: 213
Type: BOOK - Published: 2012 - Publisher: Morgan & Claypool Publishers
Provides a concise introduction to the use of Markov Decision Processes for solving probabilistic planning problems, with an emphasis on the algorithmic perspec
Language: en
Pages: 367
Pages: 367
Type: BOOK - Published: 2013-03-04 - Publisher: John Wiley & Sons
Markov Decision Processes (MDPs) are a mathematical framework for modeling sequential decision problems under uncertainty as well as reinforcement learning prob
Language: en
Pages: 204
Pages: 204
Type: BOOK - Published: 2022-06-01 - Publisher: Springer Nature
Markov Decision Processes (MDPs) are widely popular in Artificial Intelligence for modeling sequential decision-making scenarios with probabilistic dynamics. Th
Language: en
Pages: 653
Pages: 653
Type: BOOK - Published: 2012-03-05 - Publisher: Springer Science & Business Media
Reinforcement learning encompasses both a science of adaptive behavior of rational beings in uncertain environments and a computational methodology for finding
Language: en
Pages: 560
Pages: 560
Type: BOOK - Published: 2012-12-06 - Publisher: Springer Science & Business Media
Eugene A. Feinberg Adam Shwartz This volume deals with the theory of Markov Decision Processes (MDPs) and their applications. Each chapter was written by a lead