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Numerical Methods for Stochastic Control Problems in Continuous Time

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Cover of 'Numerical Methods for Stochastic Control Problems in Continuous Time'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction
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    Chapter 2 Review of Continuous Time Models
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    Chapter 3 Controlled Markov Chains
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    Chapter 4 Dynamic Programming Equations
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    Chapter 5 The Markov Chain Approximation Method: Introduction
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    Chapter 6 Construction of the Approximating Markov Chain
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    Chapter 7 Computational Methods for Controlled Markov Chains
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    Chapter 8 The Ergodic Cost Problem: Formulation and Algorithms
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    Chapter 9 Heavy Traffic and Singular Control Problems: Examples and Markov Chain Approximations
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    Chapter 10 Weak Convergence and the Characterization of Processes
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    Chapter 11 Convergence Proofs
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    Chapter 12 Convergence for Reflecting Boundaries, Singular Control and Ergodic Cost Problems
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    Chapter 13 Finite Time Problems and Nonlinear Filtering
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    Chapter 14 Problems from the Calculus of Variations
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    Chapter 15 The Viscosity Solution Approach to Proving Convergence of Numerical Schemes
Attention for Chapter 6: Construction of the Approximating Markov Chain
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Chapter title
Construction of the Approximating Markov Chain
Chapter number 6
Book title
Numerical Methods for Stochastic Control Problems in Continuous Time
Published by
Springer, New York, NY, January 1992
DOI 10.1007/978-1-4684-0441-8_6
Book ISBNs
978-1-4684-0443-2, 978-1-4684-0441-8
Authors

Harold J. Kushner, Paul G. Dupuis, Kushner, Harold J., Dupuis, Paul G.

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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 %
Researcher 1 100%
Readers by discipline Count As %
Economics, Econometrics and Finance 1 100%

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