Substitution of the Fittest: A Novel Approach for Mitigating Disengagement in Coevolutionary Genetic Algorithms
Abstract
We propose substitution of the fittest (SF), a novel technique designed to counteract the problem of disengagement in two-population competitive coevolutionary genetic algorithms. The approach presented is domain-independent and requires no calibration. In a minimal domain, we perform a controlled evaluation of the ability to maintain engagement and the capacity to discover optimal solutions. Results demonstrate that the solution discovery performance of SF is comparable with other techniques in the literature, while SF also offers benefits including a greater ability to maintain engagement and a much simpler mechanism.
Keywords
Cite
@article{arxiv.2108.03156,
title = {Substitution of the Fittest: A Novel Approach for Mitigating Disengagement in Coevolutionary Genetic Algorithms},
author = {Hugo Alcaraz-Herrera and John Cartlidge},
journal= {arXiv preprint arXiv:2108.03156},
year = {2021}
}
Comments
9 pages, authors' manuscript accepted for publication in 13th International Conference on Evolutionary Computation Theory and Algorithms (ECTA 2021)