Description: Discrete-Time Markov Control Processes by Onesimo Hernandez-Lerma, Jean B. Lasserre 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. FORMAT Paperback LANGUAGE English CONDITION Brand New Publisher Description 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. Author Biography Hernandez-Lerma, CINVESTAV-IPN, Mexico. Table of Contents 1 Introduction and Summary.- 1.1 Introduction.- 1.2 Markov control processes.- 1.3 Preliminary examples.- 1.4 Summary of the following chapters.- 2 Markov Control Processes.- 2.1 Introduction.- 2.2 Markov control processes.- 2.3 Markov policies and the Markov property.- 3 Finite-Horizon Problems.- 3.1 Introduction.- 3.2 Dynamic programming.- 3.3 The measurable selection condition.- 3.4 Variants of the DP equation.- 3.5 LQ problems.- 3.6 A consumption-investment problem.- 3.7 An inventory-production system.- 4 Infinite-Horizon Discounted-Cost Problems.- 4.1 Introduction.- 4.2 The discounted-cost optimality equation.- 4.3 Complements to the DCOE.- 4.4 Policy iteration and other approximations.- 4.5 Further optimality criteria.- 4.6 Asymptotic discount optimality.- 4.7 The discounted LQ problem.- 4.8 Concluding remarks.- 5 Long-Run Average-Cost Problems.- 5.1 Introduction.- 5.2 Canonical triplets.- 5.3 The vanishing discount approach.- 5.4 The average-cost optimality inequality.- 5.5 The average-cost optimality equation.- 5.6 Value iteration.- 5.7 Other optimality results.- 5.8 Concluding remarks.- 6 The Linear Programming Formulation.- 6.1 Introduction.- 6.2 Infinite-dimensional linear programming.- 6.3 Discounted cost.- 6.4 Average cost: preliminaries.- 6.5 Average cost: solvability.- 6.6 Further remarks.- Appendix A Miscellaneous Results.- Appendix B Conditional Expectation.- Appendix C Stochastic Kernels.- Appendix D Multifunctions and Selectors.- Appendix E Convergence of Probability Measures.- References. Promotional Springer Book Archives Long Description 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 Details ISBN1461268842 Author Jean B. Lasserre Language English Subtitle Basic Optimality Criteria Edition 95199th ISBN-10 1461268842 ISBN-13 9781461268840 Short Title DISCRETE-TIME MARKOV CONTROL P Media Book Residence US Series Stochastic Modelling and Applied Probability DEWEY 519 Series Number 30 Year 2012 Publication Date 2012-09-30 Imprint Springer-Verlag New York Inc. Place of Publication New York, NY Country of Publication United States Illustrations XIV, 216 p. AU Release Date 2012-09-30 NZ Release Date 2012-09-30 US Release Date 2012-09-30 UK Release Date 2012-09-30 Pages 216 Publisher Springer-Verlag New York Inc. Edition Description Softcover reprint of the original 1st ed. 1996 Format Paperback Alternative 9780387945798 Audience Professional & Vocational We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:137615527;
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ISBN-13: 9781461268840
Book Title: Discrete-Time Markov Control Processes
Number of Pages: 216 Pages
Language: English
Publication Name: Discrete-Time Markov Control Processes: Basic Optimality Criteria
Publisher: Springer-Verlag New York Inc.
Publication Year: 2012
Subject: Engineering & Technology, Mathematics
Item Height: 235 mm
Item Weight: 367 g
Type: Textbook
Author: Onesimo Hernandez-Lerma, Jean B. Lasserre
Item Width: 155 mm
Format: Paperback
