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Continuous State Dynamic Programming via Nonexpansive Approximation

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Author Info
John Stachurski

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Abstract

This paper studies fitted value iteration for continuous state dynamic programming using nonexpansive function approximators. A number of nonexpansive approximation schemes are discussed. The main contribution is to provide error bounds for approximate optimal policies generated by the value iteration algorithm.

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File URL: http://www.economics.unimelb.edu.au/SITE/research/workingpapers/wp06/961.pdf
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Publisher Info
Paper provided by The University of Melbourne in its series Department of Economics - Working Papers Series with number 961.

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Length: 25 pages
Date of creation: 2006
Date of revision:
Handle: RePEc:mlb:wpaper:961

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Postal: Department of Economics, The University of Melbourne, 5th Floor, Economics and Commerce Building, Victoria, 3010, Australia
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Web page: http://www.economics.unimelb.edu.au
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Related research
Keywords: Dynamic Programming; Approximation;

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Find related papers by JEL classification:
C63 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - Computational Techniques
C61 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - Optimization Techniques; Programming Models; Dynamic Analysis

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  6. Manuel S. Santos & Jesus Vigo-Aguiar, 1998. "Analysis of a Numerical Dynamic Programming Algorithm Applied to Economic Models," Econometrica, Econometric Society, vol. 66(2), pages 409-426, March.
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  9. Aruoba, S. Boragan & Fernandez-Villaverde, Jesus & Rubio-Ramirez, Juan F., 2006. "Comparing solution methods for dynamic equilibrium economies," Journal of Economic Dynamics and Control, Elsevier, vol. 30(12), pages 2477-2508, December. [Downloadable!] (restricted)
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