New Pathways in Coevolutionary Computation

Fuente: arXiv
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Main Authors: Sipper, Moshe, Moore, Jason H., Urbanowicz, Ryan J.
Format: Preprint
Published: 2024
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author Sipper, Moshe
Moore, Jason H.
Urbanowicz, Ryan J.
author_facet Sipper, Moshe
Moore, Jason H.
Urbanowicz, Ryan J.
contents The simultaneous evolution of two or more species with coupled fitness -- coevolution -- has been put to good use in the field of evolutionary computation. Herein, we present two new forms of coevolutionary algorithms, which we have recently designed and applied with success. OMNIREP is a cooperative coevolutionary algorithm that discovers both a representation and an encoding for solving a particular problem of interest. SAFE is a commensalistic coevolutionary algorithm that maintains two coevolving populations: a population of candidate solutions and a population of candidate objective functions needed to measure solution quality during evolution.
format Preprint
id arxiv_https___arxiv_org_abs_2401_10515
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle New Pathways in Coevolutionary Computation
Sipper, Moshe
Moore, Jason H.
Urbanowicz, Ryan J.
Neural and Evolutionary Computing
The simultaneous evolution of two or more species with coupled fitness -- coevolution -- has been put to good use in the field of evolutionary computation. Herein, we present two new forms of coevolutionary algorithms, which we have recently designed and applied with success. OMNIREP is a cooperative coevolutionary algorithm that discovers both a representation and an encoding for solving a particular problem of interest. SAFE is a commensalistic coevolutionary algorithm that maintains two coevolving populations: a population of candidate solutions and a population of candidate objective functions needed to measure solution quality during evolution.
title New Pathways in Coevolutionary Computation
topic Neural and Evolutionary Computing
url https://arxiv.org/abs/2401.10515