An Approximated Solution to Continuous-Time Stochastic Optimal Control Problems Through Markov Decision Chains

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An Approximated Solution to Continuous-Time Stochastic Optimal Control Problems Through Markov Decision Chains

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Jacek B. Krawczyk (Victoria University of Wellington)
Alistair Windsor (Victoria University of Wellington)

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Jacek Krawczyk

Abstract

Strategies for constructing a Markov decision chain approximating a continuous-time finite-horizon optimal control problem are investigated. Some simple, analytically soluble, examples are treated and low computational complexity is reported. Extensions to the method and implementation are discussed. In particular, relevance of the approximated solution to a stochastic renewable resource valuation problem is examined.

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Paper provided by EconWPA in its series Computational Economics with number 9710001.

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Length: 38 pages
Date of creation: 01 Oct 1997
Date of revision:
Handle: RePEc:wpa:wuwpco:9710001

Note: Type of Document - LaTeX; prepared on UNIX; to print on PostScript; pages: 38 ; figures: included
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Find related papers by JEL classification:
C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
C63 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - Computational Techniques
D92 - Microeconomics - - Intertemporal Choice and Growth - - - Intertemporal Firm Choice and Growth, Investment, or Financing
Q25 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Water

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Jacek B. Krawczyk, 2000. "A Markovian Approximated Solution To A Portfolio Management Problem," Computing in Economics and Finance 2000 233, Society for Computational Economics. [Downloadable!]
Azzato, Jeffrey D. & Krawczyk, Jacek B., 2006. "SOCSol4L: An improved MATLAB package for approximating the solution to a continuous-time stochastic optimal control problem," MPRA Paper 1179, University Library of Munich, Germany. [Downloadable!]

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