Constrained Markov Decision Processes
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Constrained Markov Decision Processes
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Author : Eitan Altman
language : en
Publisher: Routledge
Release Date : 2021-12-17
Constrained Markov Decision Processes written by Eitan Altman and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-17 with Mathematics categories.
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.
Constrained Markov Decision Processes
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Author : Eitan Altman
language : en
Publisher: CRC Press
Release Date : 1999-03-30
Constrained Markov Decision Processes written by Eitan Altman and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999-03-30 with Mathematics categories.
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.
Constrained Markov Decision Processes
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Author : E. Altman
language : en
Publisher:
Release Date : 1995
Constrained Markov Decision Processes written by E. Altman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with categories.
Constrained Markov Decision Processes With Queueing Applications
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Author : Keith W. Ross
language : en
Publisher:
Release Date : 1985
Constrained Markov Decision Processes With Queueing Applications written by Keith W. Ross and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1985 with categories.
neither on the past history nor the present state of the line-lengths.
Stochastic Processes Finance And Control
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Author : Samuel N. Cohen
language : en
Publisher: World Scientific
Release Date : 2012
Stochastic Processes Finance And Control written by Samuel N. Cohen 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 with Mathematics categories.
This book consists of a series of new, peer-reviewed papers in stochastic processes, analysis, filtering and control, with particular emphasis on mathematical finance, actuarial science and engineering. Paper contributors include colleagues, collaborators and former students of Robert Elliott, many of whom are world-leading experts and have made fundamental and significant contributions to these areas.This book provides new important insights and results by eminent researchers in the considered areas, which will be of interest to researchers and practitioners. The topics considered will be diverse in applications, and will provide contemporary approaches to the problems considered. The areas considered are rapidly evolving. This volume will contribute to their development, and present the current state-of-the-art stochastic processes, analysis, filtering and control.Contributing authors include: H Albrecher, T Bielecki, F Dufour, M Jeanblanc, I Karatzas, H-H Kuo, A Melnikov, E Platen, G Yin, Q Zhang, C Chiarella, W Fleming, D Madan, R Mamon, J Yan, V Krishnamurthy.
Markov Decision Processes With Policy Constraints
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Author : John Nafeh
language : en
Publisher:
Release Date : 1976
Markov Decision Processes With Policy Constraints written by John Nafeh and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1976 with Decision making categories.
This work is concerned with Markov Decision Processes with policy constraints. The selection of an optimum stationary policy for such processes, in the absence of policy constraints, is a problem which has received a great deal of attention, and has been satisfactorily solved. Relatively little attention has been given to the case when policy constraints are present or to the formulation of such constraints. Optimum policy sensitivity analysis is also a subject in which little has been achieved. Towards those ends, this work makes three major contributions. First, policy constraints are formulated and categorized. Secondly, a computationally efficient iterative algorithm is developed for selecting the optimum policy for completely ergodic, infinite time horizon Markov Decision Processes with policy constraints for both the risk-indifferent and risk-sensitive cases. Finally, the sensitivity of optimum policies to the policy constraints is analyzed by using the algorithm to compute the value of removing a constraint or a group of constraints. (Author).
Continuous Time Markov Decision Processes
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Author : Xianping Guo
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-09-18
Continuous Time Markov Decision Processes written by Xianping Guo 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 2009-09-18 with Mathematics categories.
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.
Markov Decision Processes In Artificial Intelligence
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Author : Olivier Sigaud
language : en
Publisher: John Wiley & Sons
Release Date : 2013-03-04
Markov Decision Processes In Artificial Intelligence written by Olivier Sigaud 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 2013-03-04 with Technology & Engineering categories.
Markov Decision Processes (MDPs) are a mathematical framework for modeling sequential decision problems under uncertainty as well as Reinforcement Learning problems. Written by experts in the field, this book provides a global view of current research using MDPs in Artificial Intelligence. It starts with an introductory presentation of the fundamental aspects of MDPs (planning in MDPs, Reinforcement Learning, Partially Observable MDPs, Markov games and the use of non-classical criteria). Then it presents more advanced research trends in the domain and gives some concrete examples using illustrative applications.
Estimation And Optimal Control For Constrained Markov Chains
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Author : D. J. Ma
language : en
Publisher:
Release Date : 1986
Estimation And Optimal Control For Constrained Markov Chains written by D. J. Ma and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1986 with categories.
Examples In Markov Decision Processes
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Author : Alexey B Piunovskiy
language : en
Publisher: World Scientific
Release Date : 2012-09-21
Examples In Markov Decision Processes written by Alexey 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 2012-09-21 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.