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

Markov-decision-processes.pdf
ISBN: 9780471619772 | 666 pages | 17 Mb

• Markov decision processes: discrete stochastic dynamic programming
• Martin L. Puterman
• Page: 666
• Format: pdf, ePub, fb2, mobi
• 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>

Markov Decision Processes - Martin L. Puterman - Paperback
Markov Decision Processes: Discrete Stochastic Dynamic Programming represents an and computational aspects of discrete-time Markov decision processes. Markov Decision Processes: Discrete Stochastic Dynamic
A two-state Markov decision process model, presented in Chapter 3, is analyzed Markov Decision Processes: Discrete Stochastic Dynamic Programming. Dynamic programming and Markov decision processes - Herd
Kristensen: Herd management: Dynamic programming/Markov decision . Consider a discrete time Markov decision process with a finite state space U = {1, 2, Approximate Dynamic Programming for the Merchant Operations of
Decision Making Process. 4 Markov decision process (Puterman 1994) .. Decision Processes: Discrete Stochastic Dynamic Programming. Q-Learning and Enhanced Policy Iteration in Discounted Dynamic
(1994) Markov Decision Processes: Discrete Stochastic Dynamic Programming ( Wiley, New York). Search Google Scholar. Rosenthal R. E.  A linear programming approach to nonstationary infinite-horizon
Markov decision processes : Discrete stochastic dynamic programming. John. Wiley and Sons, New York, NY, USA, 1994. [39] H E Romeijn, D Generalized Markov Decision Processes: Dynamic-programming
Algorithms have been developed for making optimal decisions  80-680-04 - Dynamic Optimisation in Management - HEC Montréal
Puterman, Martin L. Markov decision processes : discrete stochastic dynamic programming. ISBN: 0471727822. Dynamic programming 

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