Details
| Original language | English |
|---|---|
| Pages (from-to) | 425-487 |
| Number of pages | 63 |
| Journal | Journal of Artificial Intelligence Research |
| Volume | 75 |
| Publication status | Published - 2022 |
| Externally published | Yes |
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.
ASJC Scopus subject areas
- Computer Science(all)
- Artificial Intelligence
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In: Journal of Artificial Intelligence Research, Vol. 75, 2022, p. 425-487.
Research output: Contribution to journal › Review article › Research › peer review
}
TY - JOUR
T1 - A Survey of Methods for Automated Algorithm Configuration
AU - Schede, Elias
AU - Brandt, Jasmin
AU - Tornede, Alexander
AU - Wever, Marcel
AU - Bengs, Viktor
AU - Hüllermeier, Eyke
AU - Tierney, Kevin
N1 - Publisher Copyright: © 2022 AI Access Foundation. All rights reserved.
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85141649860&partnerID=8YFLogxK
U2 - 10.1613/jair.1.13676
DO - 10.1613/jair.1.13676
M3 - Review article
AN - SCOPUS:85141649860
VL - 75
SP - 425
EP - 487
JO - Journal of Artificial Intelligence Research
JF - Journal of Artificial Intelligence Research
SN - 1076-9757
ER -