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Using Randomization to Break the Curse of Dimensionality

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Author Info
John Rust

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Abstract

This paper introduces random versions of successive approximations and multigrid algorithms for computing approximate solutions to a class of finite and infinite horizon Markovian decision problems. The author proves that these algorithms succeed in breaking the 'curse of dimensionality' for a subclass of Markovian decision problems known as discrete decision processes.

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Publisher Info
Article provided by Econometric Society in its journal Econometrica.

Volume (Year): 65 (1997)
Issue (Month): 3 (May)
Pages: 487-516
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Handle: RePEc:ecm:emetrp:v:65:y:1997:i:3:p:487-516

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Rust, John, 1987. "Optimal Replacement of GMC Bus Engines: An Empirical Model of Harold Zurcher," Econometrica, Econometric Society, vol. 55(5), pages 999-1033, September. [Downloadable!] (restricted)
  2. Keane, Michael P & Wolpin, Kenneth I, 1994. "The Solution and Estimation of Discrete Choice Dynamic Programming Models by Simulation and Interpolation: Monte Carlo Evidence," The Review of Economics and Statistics, MIT Press, vol. 76(4), pages 648-72, November. [Downloadable!] (restricted)
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  3. Tauchen, George & Hussey, Robert, 1991. "Quadrature-Based Methods for Obtaining Approximate Solutions to Nonlinear Asset Pricing Models," Econometrica, Econometric Society, vol. 59(2), pages 371-96, March. [Downloadable!] (restricted)
  4. Hans M. Amman & David A. Kendrick, . "Computational Economics," Online economics textbooks, SUNY-Oswego, Department of Economics, number comp1, December. [Downloadable!]
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This page was last updated on 2008-7-15.

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