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Handbook of Markov Decision Processes

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Cover of 'Handbook of Markov Decision Processes'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction
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    Chapter 2 Finite State and Action MDPS
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    Chapter 3 Bias Optimality
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    Chapter 4 Singular Perturbations of Markov Chains and Decision Processes
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    Chapter 5 Average Reward Optimization Theory for Denumerable State Spaces
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    Chapter 6 Total Reward Criteria
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    Chapter 7 Mixed Criteria
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    Chapter 8 Blackwell Optimality
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    Chapter 9 The Poisson Equation for Countable Markov Chains: Probabilistic Methods and Interpretations
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    Chapter 10 Stability, Performance Evaluation, and Optimization
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    Chapter 11 Convex Analytic Methods in Markov Decision Processes
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    Chapter 12 The Linear Programming Approach
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    Chapter 13 Invariant Gambling Problems and Markov Decision Processes
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    Chapter 14 Neuro-Dynamic Programming: Overview and Recent Trends
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    Chapter 15 Markov Decision Processes in Finance and Dynamic Options
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    Chapter 16 Applications of Markov Decision Processes in Communication Networks
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    Chapter 17 Water Reservoir Applications of Markov Decision Processes
Attention for Chapter 13: Invariant Gambling Problems and Markov Decision Processes
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Chapter title
Invariant Gambling Problems and Markov Decision Processes
Chapter number 13
Book title
Handbook of Markov Decision Processes
Published by
Springer, Boston, MA, January 2002
DOI 10.1007/978-1-4615-0805-2_13
Book ISBNs
978-1-4613-5248-8, 978-1-4615-0805-2
Authors

Lester E. Dubins, Ashok P. Maitra, William D. Sudderth, Dubins, Lester E., Maitra, Ashok P., Sudderth, William D.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 1 100%
Readers by discipline Count As %
Computer Science 1 100%

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