15 citations · 40 across the 10 of their papers we have counts for
10 papers
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…
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…
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…
Objectives Are All You Need: Solving Deceptive Problems Without Explicit Diversity Maintenance
Ryan Boldi, Li Ding, Lee Spector
Navigating deceptive domains has often been a challenge in machine learning due to search algorithms getting stuck at sub-optimal local optima. Many algorithms have been proposed t…
Constructor algorithms for building unconventional computers able to solve NP-complete problems
Tony McCaffrey, Thomas E. Gorochowski, Lee Spector
Nature often builds physical structures tailored for specific information processing tasks with computations encoded using diverse phenomena. These can sometimes outperform typical…
Particularity
Lee Spector, Li Ding, Ryan Boldi
We describe a design principle for adaptive systems under which adaptation is driven by particular challenges that the environment poses, as opposed to average or otherwise aggrega…