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Markov decision processes: discrete stochastic dynamic programming Martin L. Puterman
Publisher: Wiley-Interscience

We base our model on the distinction between the decision .. Markov decision processes: discrete stochastic dynamic programming : PDF eBook Download. A wide variety of stochastic control problems can be posed as Markov decision processes. E-book Markov decision processes: Discrete stochastic dynamic programming online. However, determining an optimal control policy is intractable in many cases. Puterman Publisher: Wiley-Interscience. 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. 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. Markov Decision Processes: Discrete Stochastic Dynamic Programming . The novelty in our approach is to thoroughly blend the stochastic time with a formal approach to the problem, which preserves the Markov property. The second, semi-Markov and decision processes. May 9th, 2013 reviewer Leave a comment Go to comments. ETH - Morbidelli Group - Resources Dynamic probabilistic systems. 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.