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Author : van der Duyn Schouten (F.A.)
Publisher :
ISBN 13 :
Total Pages : 199 pages
Book Rating : 4.:/5 (989 download)
Download or read book Markov Decision Processes with Continuous Time Parameter written by van der Duyn Schouten (F.A.) and published by . This book was released on 1979 with total page 199 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : F. A. van der Duyn Schouten
Publisher :
ISBN 13 :
Total Pages : 218 pages
Book Rating : 4.:/5 (27 download)
Download or read book Markov Decision Processes with Continuous Time Parameter written by F. A. van der Duyn Schouten and published by . This book was released on 1979 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Frank A. van der Duyn Schouten
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (252 download)
Download or read book Markov Decision Processes with Continuous Time Parameter written by Frank A. van der Duyn Schouten and published by . This book was released on 1979 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Qiying Hu
Publisher : Springer Science & Business Media
ISBN 13 : 0387369511
Total Pages : 305 pages
Book Rating : 4.3/5 (873 download)
Download or read book Markov Decision Processes with Their Applications written by Qiying Hu and published by Springer Science & Business Media. This book was released on 2007-09-14 with total page 305 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.
Author : Alexey Piunovskiy
Publisher : Springer Nature
ISBN 13 : 3030549879
Total Pages : 605 pages
Book Rating : 4.0/5 (35 download)
Download or read book Continuous-Time Markov Decision Processes written by Alexey Piunovskiy and published by Springer Nature. This book was released on 2020-11-09 with total page 605 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : Nicole Bäuerle
Publisher : Springer Science & Business Media
ISBN 13 : 3642183247
Total Pages : 393 pages
Book Rating : 4.6/5 (421 download)
Download or read book Markov Decision Processes with Applications to Finance written by Nicole Bäuerle and published by Springer Science & Business Media. This book was released on 2011-06-06 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: The theory of Markov decision processes focuses on controlled Markov chains in discrete time. The authors establish the theory for general state and action spaces and at the same time show its application by means of numerous examples, mostly taken from the fields of finance and operations research. By using a structural approach many technicalities (concerning measure theory) are avoided. They cover problems with finite and infinite horizons, as well as partially observable Markov decision processes, piecewise deterministic Markov decision processes and stopping problems. The book presents Markov decision processes in action and includes various state-of-the-art applications with a particular view towards finance. It is useful for upper-level undergraduates, Master's students and researchers in both applied probability and finance, and provides exercises (without solutions).
Author : Xianping Guo
Publisher : Springer Science & Business Media
ISBN 13 : 3642025471
Total Pages : 240 pages
Book Rating : 4.6/5 (42 download)
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.
Author : Bharat T. Doshi
Publisher :
ISBN 13 :
Total Pages : 492 pages
Book Rating : 4.E/5 ( download)
Download or read book Continuous Time Control of Markov Processes on an Arbitrary State Space written by Bharat T. Doshi and published by . This book was released on 1974 with total page 492 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation studies the problem of the control of Markov processes with continuous time parameter and arbitrary state space. The economic criteria used are (a) the expected discounted return over an infinite horizon and (b) the expected average return over an infinite horizon. An extensive theory is available to treat the control problems in which either the time parameter or the state space is discrete. This dissertation extends the available theory to the general case of continuous time parameter and arbitrary state space. An application to the control of the arrival process in an M/G/1 queue is included. (Modified author abstract).
Author : Fouad Sabry
Publisher : One Billion Knowledgeable
ISBN 13 :
Total Pages : 115 pages
Book Rating : 4.:/5 (661 download)
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.
Author : Richard F. Serfozo
Publisher :
ISBN 13 :
Total Pages : 20 pages
Book Rating : 4.:/5 (227 download)
Download or read book An Equivalence Between Continuous and Discrete Time Markov Decision Processes written by Richard F. Serfozo and published by . This book was released on 1976 with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt: A continuous time Markov decision process with bounded sojourn parameters (the parameters of the exponential sojourn times in the states) is shown to be equivalent to a simpler discrete time Markov decision process. This is for both the discounted and average cost criteria on an infinite horizon. This result follows from (1) an equivalence of certain functionals of equivalent Markov processes, and (2) the property that a continuous time jump Markov process with bounded sojourn parameters is equal in distribution to a similar Markov process whose sojourn parameters are all the same. (Author).
Author : Hisashi Mine
Publisher : Elsevier Publishing Company
ISBN 13 :
Total Pages : 166 pages
Book Rating : 4.:/5 (45 download)
Download or read book Markovian Decision Processes written by Hisashi Mine and published by Elsevier Publishing Company. This book was released on 1970 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: Markovian decision processes with discounting; Markovian decision processes with no discouting; Dynamic programming viewpoint of markovian decision processes; Semi-markovian decision processes; Generalized markovian decision processes; The principle of contraction mappings in markovian decision processes.
![Download Initially Stationary [epsilon]-optimal Policies in Continuous Time Markov Decision Chains PDF Online Free](https://books.google.com/books/content/images/frontcover/ttEEAAAAIAAJ?fife=w200-h370)
Author : Mark Raphael Lembersky
Publisher :
ISBN 13 :
Total Pages : 76 pages
Book Rating : 4.F/5 ( download)
Download or read book Initially Stationary [epsilon]-optimal Policies in Continuous Time Markov Decision Chains written by Mark Raphael Lembersky and published by . This book was released on 1972 with total page 76 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : G. George Yin
Publisher : Springer Science & Business Media
ISBN 13 : 1461443466
Total Pages : 442 pages
Book Rating : 4.4/5 (614 download)
Download or read book Continuous-Time Markov Chains and Applications written by G. George Yin and published by Springer Science & Business Media. This book was released on 2012-11-14 with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gives a systematic treatment of singularly perturbed systems that naturally arise in control and optimization, queueing networks, manufacturing systems, and financial engineering. It presents results on asymptotic expansions of solutions of Komogorov forward and backward equations, properties of functional occupation measures, exponential upper bounds, and functional limit results for Markov chains with weak and strong interactions. To bridge the gap between theory and applications, a large portion of the book is devoted to applications in controlled dynamic systems, production planning, and numerical methods for controlled Markovian systems with large-scale and complex structures in the real-world problems. This second edition has been updated throughout and includes two new chapters on asymptotic expansions of solutions for backward equations and hybrid LQG problems. The chapters on analytic and probabilistic properties of two-time-scale Markov chains have been almost completely rewritten and the notation has been streamlined and simplified. This book is written for applied mathematicians, engineers, operations researchers, and applied scientists. Selected material from the book can also be used for a one semester advanced graduate-level course in applied probability and stochastic processes.
Author : A. B. Piunovskiy
Publisher : World Scientific
ISBN 13 : 1848167938
Total Pages : 308 pages
Book Rating : 4.8/5 (481 download)
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.
Author : Tomás Prieto-Rumeau
Publisher : World Scientific
ISBN 13 : 1848168489
Total Pages : 292 pages
Book Rating : 4.8/5 (481 download)
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.
Author : Xianping Guo
Publisher : Springer
ISBN 13 : 9783642025488
Total Pages : 234 pages
Book Rating : 4.0/5 (254 download)
Download or read book Continuous-Time Markov Decision Processes written by Xianping Guo and published by Springer. This book was released on 2010-04-29 with total page 234 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.
Author : G. George Yin
Publisher : Springer Science & Business Media
ISBN 13 : 0387268715
Total Pages : 354 pages
Book Rating : 4.3/5 (872 download)
Download or read book Discrete-Time Markov Chains written by G. George Yin and published by Springer Science & Business Media. This book was released on 2005-10-04 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on two-time-scale Markov chains in discrete time. Our motivation stems from existing and emerging applications in optimization and control of complex systems in manufacturing, wireless communication, and ?nancial engineering. Much of our e?ort in this book is devoted to designing system models arising from various applications, analyzing them via analytic and probabilistic techniques, and developing feasible compu- tionalschemes. Ourmainconcernistoreducetheinherentsystemcompl- ity. Although each of the applications has its own distinct characteristics, all of them are closely related through the modeling of uncertainty due to jump or switching random processes. Oneofthesalientfeaturesofthisbookistheuseofmulti-timescalesin Markovprocessesandtheirapplications. Intuitively,notallpartsorcom- nents of a large-scale system evolve at the same rate. Some of them change rapidly and others vary slowly. The di?erent rates of variations allow us to reduce complexity via decomposition and aggregation. It would be ideal if we could divide a large system into its smallest irreducible subsystems completely separable from one another and treat each subsystem indep- dently. However, this is often infeasible in reality due to various physical constraints and other considerations. Thus, we have to deal with situations in which the systems are only nearly decomposable in the sense that there are weak links among the irreducible subsystems, which dictate the oc- sional regime changes of the system. An e?ective way to treat such near decomposability is time-scale separation. That is, we set up the systems as if there were two time scales, fast vs. slow. xii Preface Followingthetime-scaleseparation,weusesingularperturbationmeth- ology to treat the underlying systems.
