Home Page

Papers

Submissions

News

Scope

Editorial Board

Announcements

Proceedings

Open Source Software

Search

Login



RSS Feed

The Cross-Entropy Method Optimizes for Quantiles

Sergiu Goschin, Ari Weinstein, Michael Littman
;
JMLR W&CP 28 (3) : 1193–1201, 2013

Abstract

Cross-entropy optimization (CE) has proven to be a powerful tool for search in control environments. In the basic scheme, a distribution over proposed solutions is repeatedly adapted by evaluating a sample of solutions and refocusing the distribution on a percentage of those with the highest scores. We show that, in the kind of noisy evaluation environments that are common in decision-making domains, this percentage-based refocusing does not optimize the expected utility of solutions, but instead a quantile metric. We provide a variant of CE (Proportional CE) that effectively optimizes the expected value. We show using variants of established noisy environments that Proportional CE can be used in place of CE and can improve solution quality.

Related Material