Was Tournament Selection All We Ever Needed? A Critical Reflection on Lexicase Selection
Alina Geiger, Martin Briesch, Dominik Sobania, Franz Rothlauf

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.…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsEvolutionary Algorithms and Applications
MethodsSparse Evolutionary Training
