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Schede, Elias; Brandt, Jasmin; Tornede, Alexander ORCID logoORCID: https://orcid.org/0000-0002-2415-2186; Wever, Marcel ORCID logoORCID: https://orcid.org/0000-0001-9782-6818; Bengs, Viktor ORCID logoORCID: https://orcid.org/0000-0001-6988-6186; Hüllermeier, Eyke ORCID logoORCID: https://orcid.org/0000-0002-9944-4108 and Tierney, Kevin (October 2022): A Survey of Methods for Automated Algorithm Configuration. In: Journal of Artificial Intelligence Research, Vol. 75: pp. 425-487

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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.

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