Econometrica Vol. 65 No. 3 1997

Using Randomization to Break the Curse of Dimensionality

John Rust

Yale University

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).

DOI

10.2307/2171751

Volume

65

Issue

3

Pages

487

Sources

bibtex:phds-export.bib crossref openalex

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