Toward Measuring the Scaling of Genetic Programming
Neural and Evolutionary Computing
2011-02-15 v1
Abstract
Several genetic programming systems are created, each solving a different problem. In these systems, the median number of generations G needed to evolve a working program is measured. The behavior of G is observed as the difficulty of the problem is increased. In these systems, the density D of working programs in the universe of all possible programs is measured. The relationship G ~ 1/sqrt(D) is observed to approximately hold for two program-like systems. For parallel systems (systems that look like several independent programs evolving in parallel), the relationship G ~ 1/(n ln n) is observed to approximately hold. Finally, systems that are anti-parallel are considered.
Cite
@article{arxiv.1102.2559,
title = {Toward Measuring the Scaling of Genetic Programming},
author = {Mike Stimpson},
journal= {arXiv preprint arXiv:1102.2559},
year = {2011}
}