The ICON Challenge on Algorithm Selection

  • Lars Kotthoff University of British Columbia
  • Barry Hurley University College Cork
  • Barry O'Sullivan Insight Centre for Data Analytics

Abstract

Algorithm selection is of increasing practical relevance in a variety of applications. Many approaches have been proposed in the literature, but their evaluations are often not comparable, making it hard to judge which approaches work best. The ICON Challenge on Algorithm Selection objectively evaluated many prominent approaches from the literature, making them directly comparable for the first time. The results show that there is still room for improvement, even for the very best approaches.
Published
2017-07-01
How to Cite
Kotthoff, L., Hurley, B., & O’Sullivan, B. (2017). The ICON Challenge on Algorithm Selection. AI Magazine, 38(2), 91-93. https://doi.org/10.1609/aimag.v38i2.2722
Section
Competition Reports