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Markov decision processes: discrete stochastic dynamic programming

Format Post in Mathematics BY Martin L. Puterman

0471619779 Shared By Guest

Markov decision processes: discrete stochastic dynamic programming Martin L. Puterman is available to download <table><tr><td colspan="2"><strong style="font-size:1.This material is available do download at niSearch.com on Martin L. Puterman's eBooks, 2em;">Markov decision processes: discrete stochastic dynamic programming</strong><br/>Martin L.Markov decision processes: discrete ... Textbook Puterman</td></tr> <tr> <td><b>Type:</b></td> <td>eBook</td> </tr> <tr> <td><b>Released:</b></td> <td>1994</td> </tr> <tr> <td><b>Publisher:</b></td> <td>Wiley-Interscience</td> </tr> <tr> <td><b>Page Count:</b></td> <td>666</td> </tr> <tr> <td><b>Format:</b></td> <td>pdf</td> </tr> <tr> <td><b>Language:</b></td> <td>English</td> </tr> <tr> <td><b>ISBN-10:</b></td> <td>0471619779</td> </tr> <tr> <td><b>ISBN-13:</b></td> <td>9780471619772</td> </tr> </table> 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. From the Publisher 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.

Markov decision processes: discrete stochastic dynamic programming

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