DocumentCode
889253
Title
Redundancy and computational efficiency in Cartesian genetic programming
Author
Miller, Julian F. ; Smith, Stephen L.
Author_Institution
Dept. of Electron., Univ. of York, Heslington, UK
Volume
10
Issue
2
fYear
2006
fDate
4/1/2006 12:00:00 AM
Firstpage
167
Lastpage
174
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% of the genes are inactive.
Keywords
genetic algorithms; graph theory; search problems; computational efficiency; evolutionary search; evolvable representations; genotype representation; graph-based Cartesian genetic programming; mutation operators; Algorithm design and analysis; Computational efficiency; Computer networks; DNA; Digital circuits; Encoding; Evolutionary computation; Genetic mutations; Genetic programming; Neural networks; Cartesian genetic programming (CGP); code bloat; genetic programming; graph-based representations; introns;
fLanguage
English
Journal_Title
Evolutionary Computation, IEEE Transactions on
Publisher
ieee
ISSN
1089-778X
Type
jour
DOI
10.1109/TEVC.2006.871253
Filename
1613935
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