Title
Emergence Of Genomic Self-Similarity In Location Independent Representations: Favoring Positive Correlation Between The Form And Quality Of Candidate Solutions
Keywords
Emergence; Genetic algorithm; Genomic self-similarity; Proportional genetic algorithm; Representation; Self-organization
Abstract
A key property for predicting 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 with the candidate solutions it encodes, the resulting genomes self-organize into self-similar structures that favor this key stochastic search property. © Springer Science + Business Media, LLC 2006.
Publication Date
3-1-2006
Publication Title
Genetic Programming and Evolvable Machines
Volume
7
Issue
1
Number of Pages
55-80
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1007/s10710-006-7011-4
Copyright Status
Unknown
Socpus ID
33646737880 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/33646737880
STARS Citation
Garibay, Ivan; Wu, Annie S.; and Garibay, Ozlem, "Emergence Of Genomic Self-Similarity In Location Independent Representations: Favoring Positive Correlation Between The Form And Quality Of Candidate Solutions" (2006). Scopus Export 2000s. 8493.
https://stars.library.ucf.edu/scopus2000/8493