2010 | OriginalPaper | Chapter
F-Race and Iterated F-Race: An Overview
Authors : Mauro Birattari, Zhi Yuan, Prasanna Balaprakash, Thomas Stützle
Published in: Experimental Methods for the Analysis of Optimization Algorithms
Publisher: Springer Berlin Heidelberg
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
Algorithms for solving hard optimization problems typically have several parameters that need to be set appropriately such that some aspect of performance is optimized. In this chapter, we review
F-Race
, a racing algorithm for the task of automatic algorithm configuration.
F-Race
is based on a statistical approach for selecting the best configuration out of a set of candidate configurations under stochastic evaluations. We review the ideas underlying this technique and discuss an extension of the initial
F-Race
algorithm, which leads to a family of algorithms that we call iterated
F-Race
. Experimental results comparing one specific implementation of iterated
F-Race
to the original
F-Race
algorithm confirm the potential of this family of algorithms.