papers

Publications (30)

q-bio.QM2015

Group Size Effect on the Success of Wolves Hunting

Ramon Escobedo, Denys Dutykh, Cristina Muro +2

Social foraging shows unexpected features such as the existence of a group size threshold to accomplish a successful hunt. Above this threshold, additional individuals do not incre…

cs.NE2021

Problem-solving benefits of down-sampled lexicase selection

Thomas Helmuth, Lee Spector

In genetic programming, an evolutionary method for producing computer programs that solve specified computational problems, parent selection is ordinarily based on aggregate measur…

cs.NE2024

Leveraging Symbolic Regression for Heuristic Design in the Traveling Thief Problem

Andrew Ni, Lee Spector

The Traveling Thief Problem is an NP-hard combination of the well known traveling salesman and knapsack packing problems. In this paper, we use symbolic regression to learn useful…

cs.NE2024

DALex: Lexicase-like Selection via Diverse Aggregation

Andrew Ni, Li Ding, Lee Spector

Lexicase selection has been shown to provide advantages over other selection algorithms in several areas of evolutionary computation and machine learning. In its standard form, lex…

cs.NE2024

Generational Computation Reduction in Informal Counterexample-Driven Genetic Programming

Thomas Helmuth, Edward Pantridge, James Gunder Frazier +1

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

cs.NE2019

Epsilon-Lexicase Selection for Regression

William La Cava, Lee Spector, Kourosh Danai

Lexicase selection is a parent selection method that considers test cases separately, rather than in aggregate, when performing parent selection. It performs well in discrete error…