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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 6: Total Reward Criteria
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