Was Tournament Selection All We Ever Needed? A Critical Reflection on Lexicase Selection

TL;DR

This paper compares tournament selection with lexicase selection, highlighting that down-sampling enhances performance and efficiency for both, with tournament selection being faster and equally effective, suggesting a need to focus more on tournament methods.

Contribution

The study demonstrates that down-sampling improves tournament selection's performance and generalization, challenging the focus solely on lexicase variants in evolutionary algorithms.

Findings

Down-sampling improves generalization and performance.

Tournament selection with down-sampling is faster and equally effective.

Down-sampling reduces code growth and increases diversity.

Abstract

The success of lexicase selection has led to various extensions, including its combination with down-sampling, which further increased performance. However, recent work found that down-sampling also leads to significant improvements in the performance of tournament selection. This raises the question of whether tournament selection combined with down-sampling is the better choice, given its faster running times. To address this question, we run a set of experiments comparing epsilon-lexicase and tournament selection with different down-sampling techniques on synthetic problems of varying noise levels and problem sizes as well as real-world symbolic regression problems. Overall, we find that down-sampling improves generalization and performance even when compared over the same number of generations. This means that down-sampling is beneficial even with way fewer fitness evaluations. Additionally, down-sampling successfully reduces code growth. We observe that population diversity increases for tournament selection when combined with down-sampling. Further, we find that tournament selection and epsilon-lexicase selection with down-sampling perform similar, while tournament selection is significantly faster. We conclude that tournament selection should be further analyzed and improved in future work instead of only focusing on the improvement of lexicase variants.