Markov Decision Processes: Discrete Stochastic Dynamic Programming
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Markov Decision Processes: Discrete Stochastic Dynamic Programming

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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 sensi...more
Published March 1st 2005 by Wiley-Interscience (first published April 29th 1994)
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