The graph-based Cartesian genetic programming system
has an unusual genotype representation with a number of
advantageous properties. It has a form of redundancy
whose role has received little attention in the
published literature. The representation has genes that
can be activated or deactivated by mutation operators
during evolution. It has been demonstrated that this
junk has a useful role and is very beneficial in
evolutionary search. The results presented demonstrate
the role of mutation and genotype length in the
evolvability of the representation. It is found that
the most evolvable representations occur when the
genotype is extremely large and in which over 95
percent of the genes are inactive.
%0 Journal Article
%1 MS:IEEETEC:06
%A Miller, Julian F.
%A Smith, Stephen L.
%D 2006
%J IEEE Transactions on Evolutionary Computation
%K (CGP), Cartesian algorithms, bloat, code genetic graph-based introns programming programming, representations,
%N 2
%P 167--174
%R doi:10.1109/TEVC.2006.871253
%T Redundancy and Computational Efficiency in Cartesian
Genetic Programming
%V 10
%X The graph-based Cartesian genetic programming system
has an unusual genotype representation with a number of
advantageous properties. It has a form of redundancy
whose role has received little attention in the
published literature. The representation has genes that
can be activated or deactivated by mutation operators
during evolution. It has been demonstrated that this
junk has a useful role and is very beneficial in
evolutionary search. The results presented demonstrate
the role of mutation and genotype length in the
evolvability of the representation. It is found that
the most evolvable representations occur when the
genotype is extremely large and in which over 95
percent of the genes are inactive.
@article{MS:IEEETEC:06,
abstract = {The graph-based Cartesian genetic programming system
has an unusual genotype representation with a number of
advantageous properties. It has a form of redundancy
whose role has received little attention in the
published literature. The representation has genes that
can be activated or deactivated by mutation operators
during evolution. It has been demonstrated that this
junk has a useful role and is very beneficial in
evolutionary search. The results presented demonstrate
the role of mutation and genotype length in the
evolvability of the representation. It is found that
the most evolvable representations occur when the
genotype is extremely large and in which over 95
percent of the genes are inactive.},
added-at = {2008-06-19T17:46:40.000+0200},
author = {Miller, Julian F. and Smith, Stephen L.},
biburl = {https://www.bibsonomy.org/bibtex/2efea83a34cdec07f88ffc614bcff9f25/brazovayeye},
doi = {doi:10.1109/TEVC.2006.871253},
interhash = {a9f09689b051acd5332d53fa4e78ac61},
intrahash = {efea83a34cdec07f88ffc614bcff9f25},
journal = {IEEE Transactions on Evolutionary Computation},
keywords = {(CGP), Cartesian algorithms, bloat, code genetic graph-based introns programming programming, representations,},
month = {April},
number = 2,
pages = {167--174},
size = {8 pages},
timestamp = {2008-06-19T17:47:22.000+0200},
title = {Redundancy and Computational Efficiency in Cartesian
Genetic Programming},
volume = 10,
year = 2006
}