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Discrete-Time Markov Control Processes: Basic Optimality Criteria (Applications of Mathematics, Volume 30) - Onesimo Hernandez-Lerma, Jean Bernard Lasserre
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Onesimo Hernandez-Lerma, Jean Bernard Lasserre:

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ISBN: 0387945792

[SR: 2015213], Hardcover, [EAN: 9780387945798], Springer, Springer, Book, [PU: Springer], Springer, 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., 173515, Engineering, 226498, Aerospace, 13647, Automotive, 226506, Bioengineering, 227539, Chemical, 227541, Civil & Environmental, 227543, Computer Modelling, 8082404011, Construction, 52168011, Design, 227544, Electrical & Electronics, 52215011, Energy Production & Extraction, 227550, Industrial, Manufacturing & Operational Systems, 107157011, Marine Engineering, 226704, Materials & Material Science, 13778, Mechanical, 226719, Military Technology, 13803, Reference, 13809, Telecommunications & Sensors, 173507, Engineering & Transportation, 1000, Subjects, 283155, Books, 13983, Probability & Statistics, 226699, Applied, 13884, Mathematics, 75, Science & Math, 1000, Subjects, 283155, Books, 14631, Technology, 75, Science & Math, 1000, Subjects, 283155, Books, 491548, Statistics, 468218, Mathematics, 468216, Science & Mathematics, 465600, New, Used & Rental Textbooks, 2349030011, Specialty Boutique, 283155, Books

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Discrete-Time Markov Control Processes: Basic Optimality Criteria (Stochastic Modelling and Applied Probability) - gebunden oder broschiert

ISBN: 0387945792

[SR: 7888973], Hardcover, [EAN: 9780387945798], Springer, Springer, Book, [PU: Springer], 1995-12-21, Springer, This book presents the first part of a planned two-volume series devoted to a systematic exposition...., 278115, Engineering & Technology, 278267, Aeronautics & Aerospace, 278271, Automotive, 278116, Bioengineering, 922268, Chemical, 278122, Civil Engineering, 922364, Education, 278150, Electrical, 278141, Electronics & Communications Engineering, 278180, Energy Technology, 922390, Engineering Physics, 922280, Engineering Skills & Design, 759164, Engineers & Inventors, 922298, Environmental, 278290, History of Engineering & Technology, 278258, Marine & Nautical, 278229, Mechanical & Materials Engineering, 922382, Military & Naval, 922344, Petroleum, Mining & Geological, 922314, Production, Manufacturing & Operational, 922260, Reference, 57, Science & Nature, 1025612, Subjects, 266239, Books, 278329, Applied Mathematics, 922530, Mathematical Modelling, 278335, Mathematics for Scientists & Engineers, 278419, Physics, 278320, Mathematics, 57, Science & Nature, 1025612, Subjects, 266239, Books, 278385, Probability & Statistics, 278320, Mathematics, 57, Science & Nature, 1025612, Subjects, 266239, Books, 922942, Maths, 922868, Popular Science, 57, Science & Nature, 1025612, Subjects, 266239, Books, 564346, Engineering, 571042, Chemical & Biochemical Engineering, 571044, Civil Engineering, 571500, Electrical Engineering, 571046, Electronics & Telecommunications Engineering, 571052, Energy Engineering, 571056, Engineering Skills & Design, 571048, Environmental Engineering, 573598, Industrial Chemistry & Manufacturing Technologies, 571050, Mechanical & Material Engineering, 564334, Scientific, Technical & Medical, 1025612, Subjects, 266239, Books, 570878, Statistics & Probability, 570874, Applied Mathematics, 564352, Mathematics, 564334, Scientific, Technical & Medical, 1025612, Subjects, 266239, Books

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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 sta mathematics,science and math,science and math,statistics,technology,textbooks Statistics, Springer

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ISBN: 0387945792

[SR: 2055152], Gebundene Ausgabe, [EAN: 9780387945798], Springer, Springer, Book, [PU: Springer], Springer, 56254011, Wahrscheinlichkeit & Statistik, 56248011, Angewandte Mathematik, 56214011, Mathematik, 56047011, Fachbücher, 54071011, Genres, 52044011, Fremdsprachige Bücher, 1320311031, Nachschlagewerke, 56441011, Technologie, 56047011, Fachbücher, 54071011, Genres, 52044011, Fremdsprachige Bücher

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Discrete-Time Markov Control Processes
Autor:

Hernandez-Lerma, O.; Lasserre, J.-B.

Titel:

Discrete-Time Markov Control Processes

ISBN-Nummer:

0387945792

This book provides a unified, comprehensive treatment of some recent theoretical developments on Markov control processes. Interest is mainly confined to MCPs with Borel state and control spaces, and possibly unbounded costs and non-compact control constraint sets. The control model studied is sufficiently general to include virtually all the usual discrete-time stochastic control models that appear in applications to engineering, economics, mathematical population processes, operations research, and management science. Much of the material appears for the first time in book form.

Detailangaben zum Buch - Discrete-Time Markov Control Processes


EAN (ISBN-13): 9780387945798
ISBN (ISBN-10): 0387945792
Gebundene Ausgabe
Erscheinungsjahr: 1996
Herausgeber: Springer-Verlag GmbH
216 Seiten
Gewicht: 0,514 kg

Buch in der Datenbank seit 28.06.2007 12:58:29
Buch zuletzt gefunden am 28.06.2016 18:13:05
ISBN/EAN: 0387945792

ISBN - alternative Schreibweisen:
0-387-94579-2, 978-0-387-94579-8

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