A Survey of Methods for Automated Algorithm Configuration

verfasst von

Elias Schede, Jasmin Brandt, Alexander Tornede, Marcel Wever, Viktor Bengs, Eyke Hüllermeier, Kevin Tierney

Abstract

Algorithm configuration (AC) is concerned with the automated search of the most suitable parameter configuration of a parametrized algorithm. There is currently a wide variety of AC problem variants and methods proposed in the literature. Existing reviews do not take into account all derivatives of the AC problem, nor do they offer a complete classification scheme. To this end, we introduce taxonomies to describe the AC problem and features of configuration methods, respectively. We review existing AC literature within the lens of our taxonomies, outline relevant design choices of configuration approaches, contrast methods and problem variants against each other, and describe the state of AC in industry. Finally, our review provides researchers and practitioners with a look at future research directions in the field of AC.

Externe Organisation(en)

Universität Bielefeld
Universität Paderborn
Ludwig-Maximilians-Universität München (LMU)

Typ

Artikel

Journal

Journal of Artificial Intelligence Research

Band

75

Seiten

425-487

Anzahl der Seiten

63

ISSN

1076-9757

Publikationsdatum

10.10.2022

Publikationsstatus

Veröffentlicht

Peer-reviewed

Ja

Elektronische Version(en)

https://doi.org/10.1613/jair.1.13676 (Zugang: Offen)