Overview

This book is devoted to a unified treatment of Competitive Markov Decision Processes. It examines these processes from the standpoints of modeling and of optimization, providing newcomers to the field with an accessible account of algorithms, theory, and applications, while also supplying specialists with a comprehensive survey of recent developments. The treatment is self-contained, requiring only some knowledge of linear algebra and real analysis. Topics covered include: Mathematical programming: Markov decision processes (the non-competitive case), and stochastic games via mathematical programming.- Existence, structure and applications: Summable stochastic games, average-reward stochastic games and applications and special classes of stochastic games.- Appendices on: matrix games, bimatrix games and nonlinear programming; a theorem of Hardy and Littlewood; Markov chains; and complex varieties and the limit discount equation.

Full Product Details

Author:   Jerzy Filar ,  Koos Vrieze
Publisher:   Springer-Verlag New York Inc.
Imprint:   Springer-Verlag New York Inc.
Edition:   1997 ed.
Dimensions:   Width: 15.60cm , Height: 2.30cm , Length: 23.40cm
Weight:   1.660kg
ISBN:  

9780387948058

ISBN 10:   0387948058
Pages:   394
Publication Date:   15 November 1996
Audience:   College/higher education ,  Professional and scholarly ,  Postgraduate, Research & Scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print  
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Table of Contents

1 Introduction.- 1.0 Background.- 1.1 Raison d’Etre and Limitations.- 1.2 A Menu of Courses and Prerequisites.- 1.3 For the Cognoscenti.- 1.4 Style and Nomenclature.- I Mathematical Programming Perspective.- 2 Markov Decision Processes: The Noncompetitive Case.- 3 Stochastic Games via Mathematical Programming.- II Existence, Structure and Applications.- 4 Summable Stochastic Games.- 5 Average Reward Stochastic Games.- 6 Applications and Special Classes of Stochastic Games.- Appendix G Matrix and Bimatrix Games and Mathematical Programming.- G.1 Introduction.- G.2 Matrix Game.- G.3 Linear Programming.- G.4 Bimatrix Games.- G.5 Mangasarian-Stone Algorithm for Bimatrix Games.- G.6 Bibliographic Notes.- Appendix H A Theorem of Hardy and Littlewood.- H.1 Introduction.- H.2 Preliminaries, Results and Examples.- H.3 Proof of the Hardy-Littlewood Theorem.- Appendix M Markov Chains.- M.1 Introduction.- M.2 Stochastic Matrix.- M.3 Invariant Distribution.- M.4 Limit Discounting.- M.5 The Fundamental Matrix.- M.6 Bibliographic Notes.- Appendix P Complex Varieties and the Limit Discount Equation.- P.1 Background.- P.2 Limit Discount Equation as a Set of Simultaneous Polynomials.- P.3 Algebraic and Analytic Varieties.- P.4 Solution of the Limit Discount Equation via Analytic Varieties.- References.

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