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

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

• Markov decision processes: discrete stochastic dynamic programming
• Martin L. Puterman
• Page: 666
• Format: pdf, ePub, mobi, fb2
• ISBN: 9780471619772
• Publisher: Wiley-Interscience

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<p>An up-to-date, unified and rigorous treatment of theoretical, computational and applied research on Markov decision process models. Concentrates on infinite-horizon discrete-time models. Discusses arbitrary state spaces, finite-horizon and continuous-time discrete-state models. Also covers modified policy iteration, multichain models with average reward criterion and sensitive optimality. Features a wealth of figures which illustrate examples and an extensive bibliography.</p> <p> From the Publisher</p> <p> An up-to-date, unified and rigorous treatment of theoretical, computational and applied research on Markov decision process models. Concentrates on infinite-horizon discrete-time models. Discusses arbitrary state spaces, finite-horizon and continuous-time discrete-state models. Also covers modified policy iteration, multichain models with average reward criterion and sensitive optimality. Features a wealth of figures which illustrate examples and an extensive bibliography. </p>

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Markov Decision Processes: Discrete Stochastic Dynamic Programming (Martin L . Puterman). Related Databases. Web of Science. You must be logged in with  Stochastic Dynamic Programming and the Control of Queueing
A path-breaking account of Markov decision processes-theory and computationThis Markov Decision Processes: Discrete Stochastic Dynamic Programming. Markov decision process - Wikipedia, the free encyclopedia
More precisely, a Markov Decision Process is a discrete time stochastic control process MDPs can be solved by linear programming or dynamic programming.

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