In recent years, several new lexicase-based selection variants have emerged due to the
success of standard lexicase selection in various application domains. For symbolic …

Genetic programming is an evolutionary approach known for its performance in program
synthesis. However, it is not yet mature enough for a practical use in real-world software …

Epsilon-lexicase selection is a parent selection method in genetic programming that has
been successfully applied to symbolic regression problems. Recently, the combination of …

Large language models have recently become known for their ability to generate computer
programs, especially through tools such as GitHub Copilot, a domain where genetic …

Genetic programming systems often use large training sets to evaluate candidate solutions,
which can be computationally expensive. Down-sampling training sets has long been used …

Genetic programming systems often use large training sets to evaluate the quality of
candidate solutions for selection. However, evaluating populations on large training sets can …

A phylogeny describes a population's evolutionary history. Evolutionary search algorithms
can perfectly track the ancestry of candidate solutions, illuminating a population's trajectory …

Genetic programming systems often use large training sets to evaluate the quality of
candidate solutions for selection, which is often computationally expensive. Down-sampling …

Lexicase selection is a parent selection method that has been successfully used in many
application domains. In recent years, several variants of lexicase selection have been …

Counterexample-driven genetic programming (CDGP) uses specifications provided as
formal constraints to generate the training cases used to evaluate evolving programs. It has …