Countable Markov Decision Chains
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Markov Decision Processes
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Author : Martin L. Puterman
language : en
Publisher: Wiley-Interscience
Release Date : 1994-04-29
Markov Decision Processes written by Martin L. Puterman and has been published by Wiley-Interscience this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994-04-29 with Mathematics categories.
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 Problems With Countable State Spaces
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Author : H. M. Dietz
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 1984-01-14
Markov Decision Problems With Countable State Spaces written by H. M. Dietz and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 1984-01-14 with Mathematics categories.
No detailed description available for "Markov Decision Problems with Countable State Spaces".
Approximating Countable Markov Chains
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Author : David Freedman
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Approximating Countable Markov Chains written by David Freedman 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.
A long time ago I started writing a book about Markov chains, Brownian motion, and diffusion. I soon had two hundred pages of manuscript and my publisher was enthusiastic. Some years and several drafts later, I had a thousand pages of manuscript, and my publisher was less enthusiastic. So we made it a trilogy: Markov Chains Brownian Motion and Diffusion Approximating Countable Markov Chains familiarly - MC, B & D, and ACM. I wrote the first two books for beginning graduate students with some knowledge of probability; if you can follow Sections 10.4 to 10.9 of Markov Chains, you're in. The first two books are quite independent of one another, and completely independent of this one, which is a monograph explaining one way to think about chains with instantaneous states. The results here are supposed to be new, except when there are specific disclaimers. It's written in the framework of Markov chains; we wanted to reprint in this volume the MC chapters needed for reference. but this proved impossible. Most of the proofs in the trilogy are new, and I tried hard to make them explicit. The old ones were often elegant, but I seldom saw what made them go. With my own, I can sometimes show you why things work. And, as I will argue in a minute, my demonstrations are easier technically. If I wrote them down well enough, you may come to agree.
Markov Chains
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Author : David Freedman
language : en
Publisher:
Release Date : 1971
Markov Chains written by David Freedman 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.
This book, part of a trilogy covering the field of Markov processes, provides a readable and constructive treatment of Markov chains. It contains some of the author's own research and many of the proofs are new. It includes material not usually available in textbooks, such as invariance principles for functionals of a Markov chain, Kolmogorov's inequality on the concentration function, the boundary, and the construction of a variety of continuous-time chains from their jump processes and holding times. (Author).
Countable Markov Decision Chains
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Author : Eugene Feinberg
language : en
Publisher: Chapman & Hall/CRC
Release Date :
Countable Markov Decision Chains written by Eugene Feinberg and has been published by Chapman & Hall/CRC this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
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.
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.
Markov Processes And Controlled Markov Chains
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Author : Zhenting Hou
language : en
Publisher: Springer Science & Business Media
Release Date : 2002-09-30
Markov Processes And Controlled Markov Chains written by Zhenting Hou 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 2002-09-30 with Business & Economics categories.
The general theory of stochastic processes and the more specialized theory of Markov processes evolved enormously in the second half of the last century. In parallel, the theory of controlled Markov chains (or Markov decision processes) was being pioneered by control engineers and operations researchers. Researchers in Markov processes and controlled Markov chains have been, for a long time, aware of the synergies between these two subject areas. However, this may be the first volume dedicated to highlighting these synergies and, almost certainly, it is the first volume that emphasizes the contributions of the vibrant and growing Chinese school of probability. The chapters that appear in this book reflect both the maturity and the vitality of modern day Markov processes and controlled Markov chains. They also will provide an opportunity to trace the connections that have emerged between the work done by members of the Chinese school of probability and the work done by the European, US, Central and South American and Asian scholars.
Markov Decision Problems With Countable State Spaces
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Author : Hans Michael Dietz
language : en
Publisher:
Release Date : 1983
Markov Decision Problems With Countable State Spaces written by Hans Michael Dietz and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1983 with Markov processes categories.
Selected Topics On Continuous Time Controlled Markov Chains And Markov Games
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Author : Tomas Prieto-rumeau
language : en
Publisher: World Scientific
Release Date : 2012-03-16
Selected Topics On Continuous Time Controlled Markov Chains And Markov Games written by Tomas Prieto-rumeau and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-03-16 with Mathematics categories.
This book concerns continuous-time controlled Markov chains, also known as continuous-time Markov decision processes. They form a class of stochastic control problems in which a single decision-maker wishes to optimize a given objective function. This book is also concerned with Markov games, where two decision-makers (or players) try to optimize their own objective function. Both decision-making processes appear in a large number of applications in economics, operations research, engineering, and computer science, among other areas.An extensive, self-contained, up-to-date analysis of basic optimality criteria (such as discounted and average reward), and advanced optimality criteria (e.g., bias, overtaking, sensitive discount, and Blackwell optimality) is presented. A particular emphasis is made on the application of the results herein: algorithmic and computational issues are discussed, and applications to population models and epidemic processes are shown.This book is addressed to students and researchers in the fields of stochastic control and stochastic games. Moreover, it could be of interest also to undergraduate and beginning graduate students because the reader is not supposed to have a high mathematical background: a working knowledge of calculus, linear algebra, probability, and continuous-time Markov chains should suffice to understand the contents of the book.