Description: Markov Decision Processes by Martin L. Puterman This book is an up-to-date, unified and rigorous treatment of theoretical, computational and applied research on Markov decision process models. The concentration of the book is on infinite-horizon discrete-time models, and it also discusses arbitrary state spaces, finite-horizon and continuous-time discrete-state models. FORMAT Paperback LANGUAGE English CONDITION Brand New Publisher Description The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "This text is unique in bringing together so many results hitherto found only in part in other texts and papers. . . . The text is fairly self-contained, inclusive of some basic mathematical results needed, and provides a rich diet of examples, applications, and exercises. The bibliographical material at the end of each chapter is excellent, not only from a historical perspective, but because it is valuable for researchers in acquiring a good perspective of the MDP research potential."—Zentralblatt fur Mathematik ". . . it is of great value to advanced-level students, researchers, and professional practitioners of this field to have now a complete volume (with more than 600 pages) devoted to this topic. . . . Markov Decision Processes: Discrete Stochastic Dynamic Programming represents an up-to-date, unified, and rigorous treatment of theoretical and computational aspects of discrete-time Markov decision processes."—Journal of the American Statistical Association Back Cover The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "This text is unique in bringing together so many results hitherto found only in part in other texts and papers. . . . The text is fairly self-contained, inclusive of some basic mathematical results needed, and provides a rich diet of examples, applications, and exercises. The bibliographical material at the end of each chapter is excellent, not only from a historical perspective, but because it is valuable for researchers in acquiring a good perspective of the MDP research potential." —Zentralblatt fur Mathematik ". . . it is of great value to advanced-level students, researchers, and professional practitioners of this field to have now a complete volume (with more than 600 pages) devoted to this topic. . . . Markov Decision Processes: Discrete Stochastic Dynamic Programming represents an up-to-date, unified, and rigorous treatment of theoretical and computational aspects of discrete-time Markov decision processes." —Journal of the American Statistical Association Flap The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "This text is unique in bringing together so many results hitherto found only in part in other texts and papers. . . . The text is fairly self-contained, inclusive of some basic mathematical results needed, and provides a rich diet of examples, applications, and exercises. The bibliographical material at the end of each chapter is excellent, not only from a historical perspective, but because it is valuable for researchers in acquiring a good perspective of the MDP research potential." -- Zentralblatt fur Mathematik ". . . it is of great value to advanced-level students, researchers, and professional practitioners of this field to have now a complete volume (with more than 600 pages) devoted to this topic. . . . Markov Decision Processes: Discrete Stochastic Dynamic Programming represents an up-to-date, unified, and rigorous treatment of theoretical and computational aspects of discrete-time Markov decision processes." -- Journal of the American Statistical Association Author Biography Martin L. Puterman, PhD, is Advisory Board Professor of Operations and Director of the Centre for Operations Excellence at The University of British Columbia in Vancouver, Canada. Table of Contents Preface. 1. Introduction. 2. Model Formulation. 3. Examples. 4. Finite-Horizon Markov Decision Processes. 5. Infinite-Horizon Models: Foundations. 6. Discounted Markov Decision Problems. 7. The Expected Total-Reward. Criterion. 8. Average Reward and Related Criteria. 9. The Average Reward Criterion-Multichain and Communicating Models. 10. Sensitive Discount Optimality. 11. Continuous-Time Models. Afterword. Notation. Appendix A. Markov Chains. Appendix B. Semicontinuous Functions. Appendix C. Normed Linear Spaces. Appendix D. Linear Programming. Bibliography. Index. Long Description The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "This text is unique in bringing together so many results hitherto found only in part in other texts and papers. . . . The text is fairly self-contained, inclusive of some basic mathematical results needed, and provides a rich diet of examples, applications, and exercises. The bibliographical material at the end of each chapter is excellent, not only from a historical perspective, but because it is valuable for researchers in acquiring a good perspective of the MDP research potential." --Zentralblatt fur Mathematik ". . . it is of great value to advanced-level students, researchers, and professional practitioners of this field to have now a complete volume (with more than 600 pages) devoted to this topic. . . . Markov Decision Processes: Discrete Stochastic Dynamic Programming represents an up-to-date, unified, and rigorous treatment of theoretical and computational aspects of discrete-time Markov decision processes." --Journal of the American Statistical Association Details ISBN0471727822 Author Martin L. Puterman Short Title MARKOV DECISION PROCESSES Series Wiley Series in Probability and Statistics Language English ISBN-10 0471727822 ISBN-13 9780471727828 Media Book Format Paperback DEWEY 519.542 Illustrations Yes Year 2005 Edition 2nd Subtitle Discrete Stochastic Dynamic Programming Place of Publication New York Country of Publication United States Replaces 9780471619772 DOI 10.1604/9780471727828 Series Number 594 UK Release Date 2005-02-25 AU Release Date 2005-03-01 NZ Release Date 2005-03-01 Pages 684 Publisher John Wiley & Sons Inc Publication Date 2005-02-25 Imprint Wiley-Interscience Alternative 9780471619772 Audience Professional & Vocational US Release Date 2005-02-25 We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:22435224;
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ISBN-13: 9780471727828
Book Title: Markov Decision Processes
Item Height: 234 mm
Item Width: 156 mm
Author: Martin L. Puterman
Publication Name: Markov Decision Processes: Discrete Stochastic Dynamic Programming
Format: Paperback
Language: English
Publisher: John Wiley & Sons Inc
Subject: Mathematics
Publication Year: 2005
Type: Textbook
Item Weight: 994 g
Number of Pages: 684 Pages
