Emergence of genomic self-similarity in location
independent representations Favoring positive
correlation between the form and quality of candidate
solutions
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-organise into
self-similar structures that favour this key stochastic
search property.
%0 Journal Article
%1 Garibay:2006:GPEM
%A Garibay, Ivan
%A Wu, Annie S.
%A Garibay, Ozlem
%D 2006
%J Genetic Programming and Evolvable Machines
%K Emergence Genomic Proportional Representation, Self-organisation, algorithm, algorithms, genetic self-similarity,
%N 1
%P 55--80
%R doi:10.1007/s10710-006-7011-4
%T Emergence of genomic self-similarity in location
independent representations Favoring positive
correlation between the form and quality of candidate
solutions
%V 7
%X 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-organise into
self-similar structures that favour this key stochastic
search property.
@article{Garibay:2006:GPEM,
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-organise into
self-similar structures that favour this key stochastic
search property.},
added-at = {2008-06-19T17:35:00.000+0200},
author = {Garibay, Ivan and Wu, Annie S. and Garibay, Ozlem},
biburl = {https://www.bibsonomy.org/bibtex/2531eec67550c833823c9bd9846af9bb9/brazovayeye},
doi = {doi:10.1007/s10710-006-7011-4},
interhash = {663c746169df5377ed1e39543837079a},
intrahash = {531eec67550c833823c9bd9846af9bb9},
issn = {1389-2576},
journal = {Genetic Programming and Evolvable Machines},
keywords = {Emergence Genomic Proportional Representation, Self-organisation, algorithm, algorithms, genetic self-similarity,},
month = {March},
notes = {white noise},
number = 1,
pages = {55--80},
size = {26 pages},
timestamp = {2008-06-19T17:40:04.000+0200},
title = {Emergence of genomic self-similarity in location
independent representations Favoring positive
correlation between the form and quality of candidate
solutions},
volume = 7,
year = 2006
}