Using Randomization to Break the Curse of Dimensionality

John Rust (jr1393@georgetown.edu), Department of Economics and University of Wisconsin

Computational Economics from University Library of Munich, Germany

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 (MDPs). We prove that these algorithms succeed in breaking the curse of dimensionality for a subclass of MDPs known as discrete decision processes (DDPs).

JEL-codes: C8 (search for similar items in EconPapers)
Date: 1994-03-29, Revised 1996-11-19
Note: TeX file, Postscript version submitted
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Related works:
Journal Article: Using Randomization to Break the Curse of Dimensionality (1997)
Working Paper: Using Randomization to Break the Curse of Dimensionality (1994)
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Persistent link: https://EconPapers.repec.org/RePEc:wpa:wuwpco:9403001

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