Title
On Favoring Positive Correlations Between Form And Quality Of Candidate Solutions Via The Emergence Of Genomic Self-Similarity
Keywords
Emergence; Genetic algorithm; Genomic self-similarity; Proportional genetic algorithm; Representation; Self-organization
Abstract
A key property for the effectiveness of stochastic search techniques, including evolutionary algorithms, is the existence of a positive correlation between the form and the quality of candidate solutions. In this paper, we show that when the ordering of genomic symbols in a genetic algorithm is completely independent of the fitness function and therefore free to evolve along the candidate solutions it encodes, the resulting genomes self-organize into self-similar structures that favor this key stochastic search property. Copyright 2005 ACM.
Publication Date
12-1-2005
Publication Title
GECCO 2005 - Genetic and Evolutionary Computation Conference
Number of Pages
1177-1184
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1145/1068009.1068204
Copyright Status
Unknown
Socpus ID
32444444501 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/32444444501
STARS Citation
Garibay, Ivan; Wu, Annie S.; and Garibay, Ozlem, "On Favoring Positive Correlations Between Form And Quality Of Candidate Solutions Via The Emergence Of Genomic Self-Similarity" (2005). Scopus Export 2000s. 3398.
https://stars.library.ucf.edu/scopus2000/3398