ASlib: A benchmark library for algorithm selection

authored by

Bernd Bischl, Pascal Kerschke, Lars Kotthoff, Marius Lindauer, Yuri Malitsky, Alexandre Fréchette, Holger Hoos, Frank Hutter, Kevin Leyton-Brown, Kevin Tierney, Joaquin Vanschoren

Abstract

The task of algorithm selection involves choosing an algorithm from a set of algorithms on a per-instance basis in order to exploit the varying performance of algorithms over a set of instances. The algorithm selection problem is attracting increasing attention from researchers and practitioners in AI. Years of fruitful applications in a number of domains have resulted in a large amount of data, but the community lacks a standard format or repository for this data. This situation makes it difficult to share and compare different approaches effectively, as is done in other, more established fields. It also unnecessarily hinders new researchers who want to work in this area. To address this problem, we introduce a standardized format for representing algorithm selection scenarios and a repository that contains a growing number of data sets from the literature. Our format has been designed to be able to express a wide variety of different scenarios. To demonstrate the breadth and power of our platform, we describe a study that builds and evaluates algorithm selection models through a common interface. The results display the potential of algorithm selection to achieve significant performance improvements across a broad range of problems and algorithms.

External Organisation(s)

Ludwig-Maximilians-Universität München (LMU)
University of Münster
University of British Columbia
University of Freiburg
IBM Research
Paderborn University
Eindhoven University of Technology (TU/e)

Type

Article

Journal

Artificial intelligence

Volume

237

Pages

41-58

No. of pages

18

ISSN

0004-3702

Publication date

04.2016

Publication status

Published

Peer reviewed

Yes

ASJC Scopus subject areas

Language and Linguistics, Linguistics and Language, Artificial Intelligence

Electronic version(s)

https://arxiv.org/abs/1506.02465 (Access: Open)
https://doi.org/10.1016/j.artint.2016.04.003 (Access: Open)