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Item Details
Title: DISCRETE-TIME MARKOV CONTROL PROCESSES
BASIC OPTIMALITY CRITERIA
By: Onesimo Hernandez-Lerma, Jean-Bernard Lasserre
Format: Paperback

List price: £108.00


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ISBN 10: 1461268842
ISBN 13: 9781461268840
Publisher: SPRINGER-VERLAG NEW YORK INC.
Pub. date: 30 September, 2012
Edition: Softcover reprint of the original 1st ed. 1996
Series: Stochastic Modelling and Applied Probability 30
Pages: 216
Synopsis: 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.
Illustrations: biography
Publication: US
Imprint: Springer-Verlag New York Inc.
Returns: Returnable
Some other items by this author:
ADAPTIVE MARKOV CONTROL PROCESSES (HB)
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AN INTEGRATED APPROACH IN PRODUCTION PLANNING AND SCHEDULING (PB)
AN INTRODUCTION TO POLYNOMIAL AND SEMI-ALGEBRAIC OPTIMIZATION (HB)
AN INTRODUCTION TO POLYNOMIAL AND SEMI-ALGEBRAIC OPTIMIZATION (PB)
CONTINUOUS-TIME MARKOV DECISION PROCESSES (HB)
CONTINUOUS-TIME MARKOV DECISION PROCESSES (PB)
DISCRETE-TIME MARKOV CONTROL PROCESSES (HB)
DISCRETE-TIME STOCHASTIC CONTROL AND DYNAMIC POTENTIAL GAMES (PB)
EVOLUTIONARY GAMES AND THE REPLICATOR DYNAMICS
EVOLUTIONARY GAMES AND THE REPLICATOR DYNAMICS (HB)
FURTHER TOPICS ON DISCRETE-TIME MARKOV CONTROL PROCESSES (HB)
FURTHER TOPICS ON DISCRETE-TIME MARKOV CONTROL PROCESSES (PB)
GEOMETRIC AND NUMERICAL FOUNDATIONS OF MOVEMENTS (HB)
HANDBOOK ON SEMIDEFINITE, CONIC AND POLYNOMIAL OPTIMIZATION
HANDBOOK ON SEMIDEFINITE, CONIC AND POLYNOMIAL OPTIMIZATION (HB)
INTRODUCTION TO OPTIMAL CONTROL THEORY
INTRODUCTION TO OPTIMAL CONTROL THEORY (HB)
LINEAR AND INTEGER PROGRAMMING VS LINEAR INTEGRATION AND COUNTING (HB)
LINEAR AND INTEGER PROGRAMMING VS LINEAR INTEGRATION AND COUNTING (PB)
MARKOV CHAINS AND INVARIANT PROBABILITIES (HB)
MARKOV CHAINS AND INVARIANT PROBABILITIES (PB)
MODERN OPTIMIZATION MODELLING TECHNIQUES (PB)
MOMENTS, POSITIVE POLYNOMIALS AND THEIR APPLICATIONS (HB)
MOMENTS, POSITIVE POLYNOMIALS AND THEIR APPLICATIONS (PB)
SELECTED TOPICS ON CONTINUOUS-TIME CONTROLLED MARKOV CHAINS AND MARKOV GAMES (HB)

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