Decision Processes In Dynamic Probabilistic Systems
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Decision Processes In Dynamic Probabilistic Systems
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Author : A.V. Gheorghe
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Decision Processes In Dynamic Probabilistic Systems written by A.V. Gheorghe and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Mathematics categories.
'Et moi - ... - si j'avait su comment en revenir. One service mathematics has rendered the je n'y serais point aile: human race. It has put common sense back where it belongs. on the topmost shelf next Jules Verne (0 the dusty canister labelled 'discarded non sense'. The series is divergent; therefore we may be able to do something with it. Eric T. Bell O. Heaviside Mathematics is a tool for thought. A highly necessary tool in a world where both feedback and non linearities abound. Similarly, all kinds of parts of mathematics serve as tools for other parts and for other sciences. Applying a simple rewriting rule to the quote on the right above one finds such statements as: 'One service topology has rendered mathematical physics .. .'; 'One service logic has rendered com puter science .. .'; 'One service category theory has rendered mathematics .. .'. All arguably true. And all statements obtainable this way form part of the raison d'etre of this series.
Decision Processes In Dynamic Probabilistic Systems
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Author : A V Gheorghe
language : en
Publisher:
Release Date : 1990-07-31
Decision Processes In Dynamic Probabilistic Systems written by A V Gheorghe and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990-07-31 with categories.
Dynamic Probabilistic Systems Volume Ii
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Author : Ronald A. Howard
language : en
Publisher: Courier Corporation
Release Date : 2013-01-18
Dynamic Probabilistic Systems Volume Ii written by Ronald A. Howard and has been published by Courier Corporation this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-01-18 with Mathematics categories.
This book is an integrated work published in two volumes. The first volume treats the basic Markov process and its variants; the second, semi-Markov and decision processes. Its intent is to equip readers to formulate, analyze, and evaluate simple and advanced Markov models of systems, ranging from genetics and space engineering to marketing. More than a collection of techniques, it constitutes a guide to the consistent application of the fundamental principles of probability and linear system theory. Author Ronald A. Howard, Professor of Management Science and Engineering at Stanford University, continues his treatment from Volume I with surveys of the discrete- and continuous-time semi-Markov processes, continuous-time Markov processes, and the optimization procedure of dynamic programming. The final chapter reviews the preceding material, focusing on the decision processes with discussions of decision structure, value and policy iteration, and examples of infinite duration and transient processes. Volume II concludes with an appendix listing the properties of congruent matrix multiplication.
Dynamic Probabilistic Systems
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Author : Ronald A. Howard
language : en
Publisher:
Release Date : 1971
Dynamic Probabilistic Systems written by Ronald A. Howard and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1971 with Markov processes categories.
Dynamic Probabilistic Systems Volume I
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Author : Ronald A. Howard
language : en
Publisher: Courier Corporation
Release Date : 2007-06-05
Dynamic Probabilistic Systems Volume I written by Ronald A. Howard and has been published by Courier Corporation this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-06-05 with Mathematics categories.
An integrated work in two volumes, this text teaches readers to formulate, analyze, and evaluate Markov models. The first volume treats basic process; the second, semi-Markov and decision processes. 1971 edition.
Dynamic Probabilistic Systems Markov Models
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Author : Ronald A. Howard
language : en
Publisher:
Release Date : 1971
Dynamic Probabilistic Systems Markov Models written by Ronald A. Howard and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1971 with Markov processes categories.
Continuous Time Markov Decision Processes
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Author : Alexey Piunovskiy
language : en
Publisher: Springer Nature
Release Date : 2020-11-09
Continuous Time Markov Decision Processes written by Alexey Piunovskiy and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-09 with Mathematics categories.
This book offers a systematic and rigorous treatment of continuous-time Markov decision processes, covering both theory and possible applications to queueing systems, epidemiology, finance, and other fields. Unlike most books on the subject, much attention is paid to problems with functional constraints and the realizability of strategies. Three major methods of investigations are presented, based on dynamic programming, linear programming, and reduction to discrete-time problems. Although the main focus is on models with total (discounted or undiscounted) cost criteria, models with average cost criteria and with impulsive controls are also discussed in depth. The book is self-contained. A separate chapter is devoted to Markov pure jump processes and the appendices collect the requisite background on real analysis and applied probability. All the statements in the main text are proved in detail. Researchers and graduate students in applied probability, operational research, statistics and engineering will find this monograph interesting, useful and valuable.
Markov Decision Processes With Their Applications
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Author : Qiying Hu
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-09-14
Markov Decision Processes With Their Applications written by Qiying Hu and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-09-14 with Business & Economics categories.
Put together by two top researchers in the Far East, this text examines Markov Decision Processes - also called stochastic dynamic programming - and their applications in the optimal control of discrete event systems, optimal replacement, and optimal allocations in sequential online auctions. This dynamic new book offers fresh applications of MDPs in areas such as the control of discrete event systems and the optimal allocations in sequential online auctions.
Markov Decision Processes
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Author : Martin L. Puterman
language : en
Publisher: John Wiley & Sons
Release Date : 2014-08-28
Markov Decision Processes written by Martin L. Puterman and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-08-28 with Mathematics categories.
The Wiley-Interscience Paperback Series consists of selected booksthat have been made more accessible to consumers in an effort toincrease global appeal and general circulation. With these newunabridged softcover volumes, Wiley hopes to extend the lives ofthese works by making them available to future generations ofstatisticians, mathematicians, and scientists. "This text is unique in bringing together so many resultshitherto found only in part in other texts and papers. . . . Thetext is fairly self-contained, inclusive of some basic mathematicalresults needed, and provides a rich diet of examples, applications,and exercises. The bibliographical material at the end of eachchapter is excellent, not only from a historical perspective, butbecause it is valuable for researchers in acquiring a goodperspective 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 havenow a complete volume (with more than 600 pages) devoted to thistopic. . . . Markov Decision Processes: Discrete Stochastic DynamicProgramming represents an up-to-date, unified, and rigoroustreatment of theoretical and computational aspects of discrete-timeMarkov decision processes." —Journal of the American Statistical Association
Examples In Markov Decision Processes
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Author : A. B. Piunovskiy
language : en
Publisher: World Scientific
Release Date : 2013
Examples In Markov Decision Processes written by A. B. Piunovskiy and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Mathematics categories.
This invaluable book provides approximately eighty examples illustrating the theory of controlled discrete-time Markov processes. Except for applications of the theory to real-life problems like stock exchange, queues, gambling, optimal search etc, the main attention is paid to counter-intuitive, unexpected properties of optimization problems. Such examples illustrate the importance of conditions imposed in the theorems on Markov Decision Processes. Many of the examples are based upon examples published earlier in journal articles or textbooks while several other examples are new. The aim was to collect them together in one reference book which should be considered as a complement to existing monographs on Markov decision processes. The book is self-contained and unified in presentation. The main theoretical statements and constructions are provided, and particular examples can be read independently of others. Examples in Markov Decision Processes is an essential source of reference for mathematicians and all those who apply the optimal control theory to practical purposes. When studying or using mathematical methods, the researcher must understand what can happen if some of the conditions imposed in rigorous theorems are not satisfied. Many examples confirming the importance of such conditions were published in different journal articles which are often difficult to find. This book brings together examples based upon such sources, along with several new ones. In addition, it indicates the areas where Markov decision processes can be used. Active researchers can refer to this book on applicability of mathematical methods and theorems. It is also suitable reading for graduate and research students where they will better understand the theory.