Using Randomization to Break the Curse of Dimensionality
AbstractThis 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 (MDPs). We prove that these algorithms succeed in breaking the curse of dimensionality for a subclass of MDPs known as discrete decision processes (DDPs).
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Bibliographic InfoPaper provided by EconWPA in its series Computational Economics with number 9403001.
Date of creation: 29 Mar 1994
Date of revision: 04 Jul 1994
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- John Rust, 1997. "Using Randomization to Break the Curse of Dimensionality," Econometrica, Econometric Society, vol. 65(3), pages 487-516, May.
- C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
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- Anderson, Evan W. & McGrattan, Ellen R. & Hansen, Lars Peter & Sargent, Thomas J., 1996.
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The Review of Economics and Statistics,
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