activity
20182026
most citedEvolving Event-driven Programs with SignalGP

21 citations · 77 across the 14 of their papers we have counts for

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Showing 2023Show all

5 papers · 1 filter

cs.NE2023★ 1 cited

Reachability Analysis for Lexicase Selection via Community Assembly Graphs

Emily Dolson, Alexander Lalejini

Fitness landscapes have historically been a powerful tool for analyzing the search space explored by evolutionary algorithms. In particular, they facilitate understanding how easil…

cs.NE2023★ 3 cited

Phylogeny-informed fitness estimation

Alexander Lalejini, Matthew Andres Moreno, Jose Guadalupe Hernandez +1

Phylogenies (ancestry trees) depict the evolutionary history of an evolving population. In evolutionary computing, a phylogeny can reveal how an evolutionary algorithm steers a pop…

cs.NE2023★ 12 cited

A Static Analysis of Informed Down-Samples

Ryan Boldi, Alexander Lalejini, Thomas Helmuth +1

We present an analysis of the loss of population-level test coverage induced by different down-sampling strategies when combined with lexicase selection. We study recorded populati…

cs.NE2023★ 2 cited

Untangling the Effects of Down-Sampling and Selection in Genetic Programming

Ryan Boldi, Ashley Bao, Martin Briesch +4

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

cs.NE2023★ 7 cited

Informed Down-Sampled Lexicase Selection: Identifying productive training cases for efficient problem solving

Ryan Boldi, Martin Briesch, Dominik Sobania +5

Genetic Programming (GP) often uses large training sets and requires all individuals to be evaluated on all training cases during selection. Random down-sampled lexicase selection…