Econometrica: May 1997, Volume 65, Issue 3

Using Randomization to Break the Curse of Dimensionality

https://doi.org/0012-9682(199705)65:3<487:URTBTC>2.0.CO;2-Z
p. 487-516

John Rust

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).
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