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
fDate :
4/1/2006 12:00:00 AM
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;
Journal_Title :
Evolutionary Computation, IEEE Transactions on
DOI :
10.1109/TEVC.2006.871253