The algorithm selection competitions 2015 and 2017

作者:

摘要

The algorithm selection problem is to choose the most suitable algorithm for solving a given problem instance. It leverages the complementarity between different approaches that is present in many areas of AI. We report on the state of the art in algorithm selection, as defined by the Algorithm Selection competitions in 2015 and 2017. The results of these competitions show how the state of the art improved over the years. We show that although performance in some cases is very good, there is still room for improvement in other cases. Finally, we provide insights into why some scenarios are hard, and pose challenges to the community on how to advance the current state of the art.

论文关键词:Algorithm Selection,Meta-Learning,Competition Analysis

论文评审过程:Received 2 May 2018, Revised 14 September 2018, Accepted 14 October 2018, Available online 4 January 2019, Version of Record 7 February 2019.

论文官网地址:https://doi.org/10.1016/j.artint.2018.10.004