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

Socpus ID

32444444501 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/32444444501

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