Download or read book Markov Decision Problems with Countable State Spaces written by H. M. Dietz and published by Walter de Gruyter GmbH & Co KG. This book was released on 1984-01-14 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: No detailed description available for "Markov Decision Problems with Countable State Spaces".
Download or read book Markov Decision Problems with Countable State Spaces written by Hans Michael Dietz and published by . This book was released on 1983 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Markov decision problems with countable state spaces written by Hans Michael Dietz and published by . This book was released on 1983 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Constrained Markov Decision Processes written by Eitan Altman and published by CRC Press. This book was released on 1999-03-30 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a unified approach for the study of constrained Markov decision processes with a finite state space and unbounded costs. Unlike the single controller case considered in many other books, the author considers a single controller with several objectives, such as minimizing delays and loss, probabilities, and maximization of throughputs. It is desirable to design a controller that minimizes one cost objective, subject to inequality constraints on other cost objectives. This framework describes dynamic decision problems arising frequently in many engineering fields. A thorough overview of these applications is presented in the introduction. The book is then divided into three sections that build upon each other. The first part explains the theory for the finite state space. The author characterizes the set of achievable expected occupation measures as well as performance vectors, and identifies simple classes of policies among which optimal policies exist. This allows the reduction of the original dynamic into a linear program. A Lagranian approach is then used to derive the dual linear program using dynamic programming techniques. In the second part, these results are extended to the infinite state space and action spaces. The author provides two frameworks: the case where costs are bounded below and the contracting framework. The third part builds upon the results of the first two parts and examines asymptotical results of the convergence of both the value and the policies in the time horizon and in the discount factor. Finally, several state truncation algorithms that enable the approximation of the solution of the original control problem via finite linear programs are given.
Download or read book 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 223 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the first part of a planned two-volume series devoted to a systematic exposition of some recent developments in the theory of discrete-time Markov control processes (MCPs). Interest is mainly confined to MCPs with Borel state and control (or action) spaces, and possibly unbounded costs and noncompact control constraint sets. MCPs are a class of stochastic control problems, also known as Markov decision processes, controlled Markov processes, or stochastic dynamic pro grams; sometimes, particularly when the state space is a countable set, they are also called Markov decision (or controlled Markov) chains. Regardless of the name used, MCPs appear in many fields, for example, engineering, economics, operations research, statistics, renewable and nonrenewable re source management, (control of) epidemics, etc. However, most of the lit erature (say, at least 90%) is concentrated on MCPs for which (a) the state space is a countable set, and/or (b) the costs-per-stage are bounded, and/or (c) the control constraint sets are compact. But curiously enough, the most widely used control model in engineering and economics--namely the LQ (Linear system/Quadratic cost) model-satisfies none of these conditions. Moreover, when dealing with "partially observable" systems) a standard approach is to transform them into equivalent "completely observable" sys tems in a larger state space (in fact, a space of probability measures), which is uncountable even if the original state process is finite-valued.
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.
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.
Download or read book Markov Decision Processes and Stochastic Positional Games written by Dmitrii Lozovanu and published by Springer Nature. This book was released on 2024-02-13 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent findings and results concerning the solutions of especially finite state-space Markov decision problems and determining Nash equilibria for related stochastic games with average and total expected discounted reward payoffs. In addition, it focuses on a new class of stochastic games: stochastic positional games that extend and generalize the classic deterministic positional games. It presents new algorithmic results on the suitable implementation of quasi-monotonic programming techniques. Moreover, the book presents applications of positional games within a class of multi-objective discrete control problems and hierarchical control problems on networks. Given its scope, the book will benefit all researchers and graduate students who are interested in Markov theory, control theory, optimization and games.
Download or read book Labelled Markov Processes written by Prakash Panangaden and published by Imperial College Press. This book was released on 2009 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: Labelled Markov processes are probabilistic versions of labelled transition systems with continuous state spaces. The book covers basic probability and measure theory on continuous state spaces and then develops the theory of LMPs.
Download or read book Structural Induction on Partial Algebras II written by H. Reichel and published by Walter de Gruyter GmbH & Co KG. This book was released on 2022-10-24 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A Model Theoretic Oriented Approach to Partial Algebras written by P. Burmeister and published by Walter de Gruyter GmbH & Co KG. This book was released on 1986-12-31 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: No detailed description available for "A Model Theoretic Oriented Approach to Partial Algebras".
Download or read book Andreotti Grauert Theory by Integral Formulas written by G. M. Henkin and published by Walter de Gruyter GmbH & Co KG. This book was released on 2022-01-19 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Advances in Mathematical Optimization written by J. Guddat et al. and published by Walter de Gruyter GmbH & Co KG. This book was released on 2022-01-19 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Systems Analysis and Simulation 1988 I Theory and Foundations Proceedings of the International Symposium held in Berlin GDR September 12 16 1988 written by Achim Sydow and published by Walter de Gruyter GmbH & Co KG. This book was released on 2022-01-19 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Constrained Markov Decision Processes written by Eitan Altman and published by Routledge. This book was released on 2021-12-17 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a unified approach for the study of constrained Markov decision processes with a finite state space and unbounded costs. Unlike the single controller case considered in many other books, the author considers a single controller with several objectives, such as minimizing delays and loss, probabilities, and maximization of throughputs. It is desirable to design a controller that minimizes one cost objective, subject to inequality constraints on other cost objectives. This framework describes dynamic decision problems arising frequently in many engineering fields. A thorough overview of these applications is presented in the introduction. The book is then divided into three sections that build upon each other.
Download or read book Foundations of Reinforcement Learning with Applications in Finance written by Ashwin Rao and published by CRC Press. This book was released on 2022-12-16 with total page 658 pages. Available in PDF, EPUB and Kindle. Book excerpt: Foundations of Reinforcement Learning with Applications in Finance aims to demystify Reinforcement Learning, and to make it a practically useful tool for those studying and working in applied areas — especially finance. Reinforcement Learning is emerging as a powerful technique for solving a variety of complex problems across industries that involve Sequential Optimal Decisioning under Uncertainty. Its penetration in high-profile problems like self-driving cars, robotics, and strategy games points to a future where Reinforcement Learning algorithms will have decisioning abilities far superior to humans. But when it comes getting educated in this area, there seems to be a reluctance to jump right in, because Reinforcement Learning appears to have acquired a reputation for being mysterious and technically challenging. This book strives to impart a lucid and insightful understanding of the topic by emphasizing the foundational mathematics and implementing models and algorithms in well-designed Python code, along with robust coverage of several financial trading problems that can be solved with Reinforcement Learning. This book has been created after years of iterative experimentation on the pedagogy of these topics while being taught to university students as well as industry practitioners. Features Focus on the foundational theory underpinning Reinforcement Learning and software design of the corresponding models and algorithms Suitable as a primary text for courses in Reinforcement Learning, but also as supplementary reading for applied/financial mathematics, programming, and other related courses Suitable for a professional audience of quantitative analysts or data scientists Blends theory/mathematics, programming/algorithms and real-world financial nuances while always striving to maintain simplicity and to build intuitive understanding To access the code base for this book, please go to: https://github.com/TikhonJelvis/RL-book
Download or read book Nonlinear and Convex Analysis written by Bor-Luh Lin and published by CRC Press. This book was released on 2023-05-31 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains expanded versions of the talks given at the conference held in honour of professor Ky Fan in California in 1985, as well as papers on nonlinear and convex analysis as contributions to Ky Fan. It also includes a list of publications by Ky Fan.
