The Algorithm Selection Competitions 2015 and 2017

TL;DR

This paper reviews the progress and challenges in algorithm selection, based on the 2015 and 2017 competitions, highlighting improvements, remaining difficulties, and future research directions.

Contribution

It provides an overview of the state of the art in algorithm selection through competition results and discusses challenges and opportunities for future advancements.

Findings

Performance has improved over the years.

Some scenarios remain difficult for current methods.

There is still significant room for improvement in certain cases.

Abstract

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.