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Erschienen in:
2010 | OriginalPaper | Buchkapitel
F-Race and Iterated F-Race: An Overview
verfasst von : Mauro Birattari, Zhi Yuan, Prasanna Balaprakash, Thomas Stützle
Erschienen in: Experimental Methods for the Analysis of Optimization Algorithms
Verlag: Springer Berlin Heidelberg
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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.