IEEE Transactions on Evolutionary Computation · 2006 · 269 citations · 29 references
ArchitectureEvolutionary BiologyEvolutionary GeneticsEvolutionary TheoryMicroevolutionCrossover OperatorsEvolutionary ComputationEvolutionary OptimizationGenetic AlgorithmsGenetic ProgrammingMutation OperatorsCartesian Genetic ProgrammingComputational EfficiencyEvolutionary AlgorithmsEvolutionary SearchGenetic Programming MutationGenotype EncodingMutationRepresentation In Evolutionary Algorithms
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.
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