Using Randomization to Break the Curse of Dimensionality

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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Year of publication:	1997
Authors:	Rust, John
Published in:	Econometrica. - Econometric Society. - Vol. 65.1997, 3, p. 487-516
Publisher:	Econometric Society

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005702099