Selected Topics on Continuous-time Controlled Markov Chains and Markov Games

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Publisher : World Scientific
ISBN 13 : 1848168489
Total Pages : 292 pages
Book Rating : 4.8/5 (481 download)

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Book Synopsis Selected Topics on Continuous-time Controlled Markov Chains and Markov Games by : Tomás Prieto-Rumeau

Download or read book Selected Topics on Continuous-time Controlled Markov Chains and Markov Games written by Tomás Prieto-Rumeau and published by World Scientific. This book was released on 2012 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Topics in Controlled Markov Chains

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Publisher :
ISBN 13 : 9780608035956
Total Pages : 191 pages
Book Rating : 4.0/5 (359 download)

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Book Synopsis Topics in Controlled Markov Chains by : Vivek S. Borkar

Download or read book Topics in Controlled Markov Chains written by Vivek S. Borkar and published by . This book was released on 1991 with total page 191 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Markov Processes and Controlled Markov Chains

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Publisher : Springer Science & Business Media
ISBN 13 : 146130265X
Total Pages : 501 pages
Book Rating : 4.4/5 (613 download)

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Book Synopsis Markov Processes and Controlled Markov Chains by : Zhenting Hou

Download or read book Markov Processes and Controlled Markov Chains written by Zhenting Hou and published by Springer Science & Business Media. This book was released on 2013-12-01 with total page 501 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Topics in Controlled Markov Chains

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Publisher : Longman Sc & Tech
ISBN 13 : 9780470217603
Total Pages : 179 pages
Book Rating : 4.2/5 (176 download)

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Book Synopsis Topics in Controlled Markov Chains by : Vivek S. Borkar

Download or read book Topics in Controlled Markov Chains written by Vivek S. Borkar and published by Longman Sc & Tech. This book was released on 1991 with total page 179 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Cont Markov Chains

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Publisher : CRC Press
ISBN 13 : 9780582068216
Total Pages : 196 pages
Book Rating : 4.0/5 (682 download)

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Book Synopsis Cont Markov Chains by : Borkar

Download or read book Cont Markov Chains written by Borkar and published by CRC Press. This book was released on 1991-04-30 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides a novel treatment of many problems in controlled Markov chains based on occupation measures and convex analysis. Includes a rederivation of many classical results, a general treatment of the ergodic control problems and an extensive study of the asymptotic behavior of the self-tuning adaptive controller and its variant, the Kumar-Becker-Lin scheme. Also includes a novel treatment of some multiobjective control problems, inaccessible to traditional methods. Annotation copyrighted by Book News, Inc., Portland, OR

Further Topics on Discrete-Time Markov Control Processes

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Publisher : Springer Science & Business Media
ISBN 13 : 1461205611
Total Pages : 286 pages
Book Rating : 4.4/5 (612 download)

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Book Synopsis Further Topics on Discrete-Time Markov Control Processes by : Onesimo Hernandez-Lerma

Download or read book Further Topics on Discrete-Time Markov Control Processes written by Onesimo Hernandez-Lerma and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: Devoted to a systematic exposition of some recent developments in the theory of discrete-time Markov control processes, the text is mainly confined to MCPs with Borel state and control spaces. Although the book follows on from the author's earlier work, an important feature of this volume is that it is self-contained and can thus be read independently of the first. The control model studied is sufficiently general to include virtually all the usual discrete-time stochastic control models that appear in applications to engineering, economics, mathematical population processes, operations research, and management science.

Controlled Markov Chains, Graphs and Hamiltonicity

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Publisher : Now Publishers Inc
ISBN 13 : 1601980884
Total Pages : 95 pages
Book Rating : 4.6/5 (19 download)

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Book Synopsis Controlled Markov Chains, Graphs and Hamiltonicity by : Jerzy A. Filar

Download or read book Controlled Markov Chains, Graphs and Hamiltonicity written by Jerzy A. Filar and published by Now Publishers Inc. This book was released on 2007 with total page 95 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Controlled Markov Chains, Graphs & Hamiltonicity" summarizes a line of research that maps certain classical problems of discrete mathematics--such as the Hamiltonian cycle and the Traveling Salesman problems--into convex domains where continuum analysis can be carried out. (Mathematics)

Controlled Markov Processes and Viscosity Solutions

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Publisher : Springer Science & Business Media
ISBN 13 : 0387310711
Total Pages : 436 pages
Book Rating : 4.3/5 (873 download)

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Book Synopsis Controlled Markov Processes and Viscosity Solutions by : Wendell H. Fleming

Download or read book Controlled Markov Processes and Viscosity Solutions written by Wendell H. Fleming and published by Springer Science & Business Media. This book was released on 2006-02-04 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an introduction to optimal stochastic control for continuous time Markov processes and the theory of viscosity solutions. It covers dynamic programming for deterministic optimal control problems, as well as to the corresponding theory of viscosity solutions. New chapters in this second edition introduce the role of stochastic optimal control in portfolio optimization and in pricing derivatives in incomplete markets and two-controller, zero-sum differential games.

Optimization and Games for Controllable Markov Chains

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Publisher : Springer Nature
ISBN 13 : 3031435753
Total Pages : 340 pages
Book Rating : 4.0/5 (314 download)

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Book Synopsis Optimization and Games for Controllable Markov Chains by : Julio B. Clempner

Download or read book Optimization and Games for Controllable Markov Chains written by Julio B. Clempner and published by Springer Nature. This book was released on 2023-12-13 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book considers a class of ergodic finite controllable Markov's chains. The main idea behind the method, described in this book, is to develop the original discrete optimization problems (or game models) in the space of randomized formulations, where the variables stand in for the distributions (mixed strategies or preferences) of the original discrete (pure) strategies in the use. The following suppositions are made: a finite state space, a limited action space, continuity of the probabilities and rewards associated with the actions, and a necessity for accessibility. These hypotheses lead to the existence of an optimal policy. The best course of action is always stationary. It is either simple (i.e., nonrandomized stationary) or composed of two nonrandomized policies, which is equivalent to randomly selecting one of two simple policies throughout each epoch by tossing a biased coin. As a bonus, the optimization procedure just has to repeatedly solve the time-average dynamic programming equation, making it theoretically feasible to choose the optimum course of action under the global restriction. In the ergodic cases the state distributions, generated by the corresponding transition equations, exponentially quickly converge to their stationary (final) values. This makes it possible to employ all widely used optimization methods (such as Gradient-like procedures, Extra-proximal method, Lagrange's multipliers, Tikhonov's regularization), including the related numerical techniques. In the book we tackle different problems and theoretical Markov models like controllable and ergodic Markov chains, multi-objective Pareto front solutions, partially observable Markov chains, continuous-time Markov chains, Nash equilibrium and Stackelberg equilibrium, Lyapunov-like function in Markov chains, Best-reply strategy, Bayesian incentive-compatible mechanisms, Bayesian Partially Observable Markov Games, bargaining solutions for Nash and Kalai-Smorodinsky formulations, multi-traffic signal-control synchronization problem, Rubinstein's non-cooperative bargaining solutions, the transfer pricing problem as bargaining.

Continuous-Time Markov Decision Processes

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Publisher : Springer Science & Business Media
ISBN 13 : 3642025471
Total Pages : 240 pages
Book Rating : 4.6/5 (42 download)

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Book Synopsis Continuous-Time Markov Decision Processes by : Xianping Guo

Download or read book Continuous-Time Markov Decision Processes written by Xianping Guo and published by Springer Science & Business Media. This book was released on 2009-09-18 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: Continuous-time Markov decision processes (MDPs), also known as controlled Markov chains, are used for modeling decision-making problems that arise in operations research (for instance, inventory, manufacturing, and queueing systems), computer science, communications engineering, control of populations (such as fisheries and epidemics), and management science, among many other fields. This volume provides a unified, systematic, self-contained presentation of recent developments on the theory and applications of continuous-time MDPs. The MDPs in this volume include most of the cases that arise in applications, because they allow unbounded transition and reward/cost rates. Much of the material appears for the first time in book form.

Examples in Markov Decision Processes

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Publisher : World Scientific
ISBN 13 : 1848167938
Total Pages : 308 pages
Book Rating : 4.8/5 (481 download)

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Book Synopsis Examples in Markov Decision Processes by : A. B. Piunovskiy

Download or read book Examples in Markov Decision Processes written by A. B. Piunovskiy and published by World Scientific. This book was released on 2013 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Foundations of Average-Cost Nonhomogeneous Controlled Markov Chains

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Publisher :
ISBN 13 : 9783030566791
Total Pages : 0 pages
Book Rating : 4.5/5 (667 download)

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Book Synopsis Foundations of Average-Cost Nonhomogeneous Controlled Markov Chains by : Xi-Ren Cao

Download or read book Foundations of Average-Cost Nonhomogeneous Controlled Markov Chains written by Xi-Ren Cao and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Springer brief addresses the challenges encountered in the study of the optimization of time-nonhomogeneous Markov chains. It develops new insights and new methodologies for systems in which concepts such as stationarity, ergodicity, periodicity and connectivity do not apply. This brief introduces the novel concept of confluencity and applies a relative optimization approach. It develops a comprehensive theory for optimization of the long-run average of time-nonhomogeneous Markov chains. The book shows that confluencity is the most fundamental concept in optimization, and that relative optimization is more suitable for treating the systems under consideration than standard ideas of dynamic programming. Using confluencity and relative optimization, the author classifies states as confluent or branching and shows how the under-selectivity issue of the long-run average can be easily addressed, multi-class optimization implemented, and Nth biases and Blackwell optimality conditions derived. These results are presented in a book for the first time and so may enhance the understanding of optimization and motivate new research ideas in the area.

Markov Decision Process

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Publisher : One Billion Knowledgeable
ISBN 13 :
Total Pages : 115 pages
Book Rating : 4.:/5 (661 download)

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Book Synopsis Markov Decision Process by : Fouad Sabry

Download or read book Markov Decision Process written by Fouad Sabry and published by One Billion Knowledgeable. This book was released on 2023-06-27 with total page 115 pages. Available in PDF, EPUB and Kindle. Book excerpt: What Is Markov Decision Process A discrete-time stochastic control process is referred to as a Markov decision process (MDP) in the field of mathematics. It offers a mathematical framework for modeling decision making in scenarios in which the outcomes are partially controlled by a decision maker and partly determined by random chance. The study of optimization issues that can be handled by dynamic programming lends itself well to the use of MDPs. At the very least, MDPs were recognized to exist in the 1950s. Ronald Howard's book, published in 1960 and titled Dynamic Programming and Markov Processes, is credited for initiating a core body of study on Markov decision processes. They have applications in a wide variety of fields, including as robotics, automatic control, economics, and manufacturing, among others. Because Markov decision processes are an extension of Markov chains, the Russian mathematician Andrey Markov is where the term "Markov decision processes" (MDPs) originated. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Markov decision process Chapter 2: Markov chain Chapter 3: Reinforcement learning Chapter 4: Bellman equation Chapter 5: Admissible decision rule Chapter 6: Partially observable Markov decision process Chapter 7: Temporal difference learning Chapter 8: Multi-armed bandit Chapter 9: Optimal stopping Chapter 10: Metropolis-Hastings algorithm (II) Answering the public top questions about markov decision process. (III) Real world examples for the usage of markov decision process in many fields. (IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of markov decision process' technologies. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of markov decision process. What is Artificial Intelligence Series The artificial intelligence book series provides comprehensive coverage in over 200 topics. Each ebook covers a specific Artificial Intelligence topic in depth, written by experts in the field. The series aims to give readers a thorough understanding of the concepts, techniques, history and applications of artificial intelligence. Topics covered include machine learning, deep learning, neural networks, computer vision, natural language processing, robotics, ethics and more. The ebooks are written for professionals, students, and anyone interested in learning about the latest developments in this rapidly advancing field. The artificial intelligence book series provides an in-depth yet accessible exploration, from the fundamental concepts to the state-of-the-art research. With over 200 volumes, readers gain a thorough grounding in all aspects of Artificial Intelligence. The ebooks are designed to build knowledge systematically, with later volumes building on the foundations laid by earlier ones. This comprehensive series is an indispensable resource for anyone seeking to develop expertise in artificial intelligence.

Markov Decision Processes with Their Applications

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Publisher : Springer
ISBN 13 : 9781441942388
Total Pages : 0 pages
Book Rating : 4.9/5 (423 download)

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Book Synopsis Markov Decision Processes with Their Applications by : Qiying Hu

Download or read book Markov Decision Processes with Their Applications written by Qiying Hu and published by Springer. This book was released on 2010-11-19 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Controlled Markov Processes

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Publisher : Springer
ISBN 13 :
Total Pages : 320 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Controlled Markov Processes by : Evgeniĭ Borisovich Dynkin

Download or read book Controlled Markov Processes written by Evgeniĭ Borisovich Dynkin and published by Springer. This book was released on 1979 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is devoted to the systematic exposition of the contemporary theory of controlled Markov processes with discrete time parameter or in another termi nology multistage Markovian decision processes. We discuss the applications of this theory to various concrete problems. Particular attention is paid to mathe matical models of economic planning, taking account of stochastic factors. The authors strove to construct the exposition in such a way that a reader interested in the applications can get through the book with a minimal mathe matical apparatus. On the other hand, a mathematician will find, in the appropriate chapters, a rigorous theory of general control models, based on advanced measure theory, analytic set theory, measurable selection theorems, and so forth. We have abstained from the manner of presentation of many mathematical monographs, in which one presents immediately the most general situation and only then discusses simpler special cases and examples. Wishing to separate out difficulties, we introduce new concepts and ideas in the simplest setting, where they already begin to work. Thus, before considering control problems on an infinite time interval, we investigate in detail the case of the finite interval. Here we first study in detail models with finite state and action spaces-a case not requiring a departure from the realm of elementary mathematics, and at the same time illustrating the most important principles of the theory.

Optimization, Control, and Applications of Stochastic Systems

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Publisher : Springer Science & Business Media
ISBN 13 : 0817683372
Total Pages : 331 pages
Book Rating : 4.8/5 (176 download)

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Book Synopsis Optimization, Control, and Applications of Stochastic Systems by : Daniel Hernández-Hernández

Download or read book Optimization, Control, and Applications of Stochastic Systems written by Daniel Hernández-Hernández and published by Springer Science & Business Media. This book was released on 2012-08-15 with total page 331 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume provides a general overview of discrete- and continuous-time Markov control processes and stochastic games, along with a look at the range of applications of stochastic control and some of its recent theoretical developments. These topics include various aspects of dynamic programming, approximation algorithms, and infinite-dimensional linear programming. In all, the work comprises 18 carefully selected papers written by experts in their respective fields. Optimization, Control, and Applications of Stochastic Systems will be a valuable resource for all practitioners, researchers, and professionals in applied mathematics and operations research who work in the areas of stochastic control, mathematical finance, queueing theory, and inventory systems. It may also serve as a supplemental text for graduate courses in optimal control and dynamic games.

Handbook of Markov Decision Processes

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Publisher : Springer Science & Business Media
ISBN 13 : 1461508053
Total Pages : 560 pages
Book Rating : 4.4/5 (615 download)

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Book Synopsis Handbook of Markov Decision Processes by : Eugene A. Feinberg

Download or read book Handbook of Markov Decision Processes written by Eugene A. Feinberg and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt: Eugene A. Feinberg Adam Shwartz This volume deals with the theory of Markov Decision Processes (MDPs) and their applications. Each chapter was written by a leading expert in the re spective area. The papers cover major research areas and methodologies, and discuss open questions and future research directions. The papers can be read independently, with the basic notation and concepts ofSection 1.2. Most chap ters should be accessible by graduate or advanced undergraduate students in fields of operations research, electrical engineering, and computer science. 1.1 AN OVERVIEW OF MARKOV DECISION PROCESSES The theory of Markov Decision Processes-also known under several other names including sequential stochastic optimization, discrete-time stochastic control, and stochastic dynamic programming-studiessequential optimization ofdiscrete time stochastic systems. The basic object is a discrete-time stochas tic system whose transition mechanism can be controlled over time. Each control policy defines the stochastic process and values of objective functions associated with this process. The goal is to select a "good" control policy. In real life, decisions that humans and computers make on all levels usually have two types ofimpacts: (i) they cost orsavetime, money, or other resources, or they bring revenues, as well as (ii) they have an impact on the future, by influencing the dynamics. In many situations, decisions with the largest immediate profit may not be good in view offuture events. MDPs model this paradigm and provide results on the structure and existence of good policies and on methods for their calculation.