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SOCSol4L: An improved MATLAB package for approximating the solution to a continuous-time stochastic optimal control problem

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Author Info
Azzato, Jeffrey D.
Krawczyk, Jacek B.

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Abstract

Computing the solution to a stochastic optimal control problem is difficult. A method of approximating a solution to a given stochastic optimal control problem using Markov chains was developed in [Kra01]. This paper describes a suite of MATLAB functions implementing this method of approximating a solution to a given continuous stochastic optimal control problem.

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File URL: http://mpra.ub.uni-muenchen.de/1179/
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File URL: http://mpra.ub.uni-muenchen.de/8946/
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Publisher Info
Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 1179.

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Date of creation: Dec 2006
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Handle: RePEc:pra:mprapa:1179

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Related research
Keywords: Computational techniques Economic software Computational methods in stochastic optimal control Computational economics Approximating Markov decision chains

Find related papers by JEL classification:
C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software
C63 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - Computational Techniques

This paper has been announced in the following NEP Reports:

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  1. Jacek B. Krawczyk & Alistair Windsor, 1997. "An Approximated Solution to Continuous-Time Stochastic Optimal Control Problems Through Markov Decision Chains," Computational Economics 9710001, EconWPA. [Downloadable!]
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