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Markov decision processes: discrete stochastic dynamic programming by Martin L. Puterman

Markov decision processes: discrete stochastic dynamic programming Martin L. Puterman ebook
ISBN: 0471619779, 9780471619772
Page: 666
Publisher: Wiley-Interscience
Format: pdf

Markov decision processes (MDPs), also called stochastic dynamic programming, were first studied in the 1960s. We base our model on the distinction between the decision .. The novelty in our approach is to thoroughly blend the stochastic time with a formal approach to the problem, which preserves the Markov property. Models are developed in discrete time as For these models, however, it seeks to be as comprehensive as possible, although finite horizon models in discrete time are not developed, since they are largely described in existing literature. This book presents a unified theory of dynamic programming and Markov decision processes and its application to a major field of operations research and operations management: inventory control. A path-breaking account of Markov decision processes-theory and computation. A tutorial on hidden Markov models and selected applications in speech recognition. White: 9780471936275: Amazon.com. Handbook of Markov Decision Processes : Methods and Applications . MDPs can be used to model and solve dynamic decision-making Markov Decision Processes With Their Applications examines MDPs and their applications in the optimal control of discrete event systems (DESs), optimal replacement, and optimal allocations in sequential online auctions. Markov Decision Processes: Discrete Stochastic Dynamic Programming. Downloads Handbook of Markov Decision Processes : Methods andMarkov decision processes: discrete stochastic dynamic programming. 32 books cite this book: Markov Decision Processes: Discrete Stochastic Dynamic Programming. We modeled this problem as a sequential decision process and used stochastic dynamic programming in order to find the optimal decision at each decision stage. LINK: Download Stochastic Dynamic Programming and the C… eBook (PDF). Proceedings of the IEEE, 77(2): 257-286..