Genetic programming (videotape): the movie
Genetic programming (videotape): the movie
Genetic Programming and Data Structures: Genetic Programming + Data Structures = Automatic Programming!
Grammatical Evolution: Evolving Programs for an Arbitrary Language
EuroGP '98 Proceedings of the First European Workshop on Genetic Programming
Neutrality and the Evolvability of Boolean Function Landscape
EuroGP '01 Proceedings of the 4th European Conference on Genetic Programming
Crossover in Grammatical Evolution: The Search Continues
EuroGP '01 Proceedings of the 4th European Conference on Genetic Programming
Some Experimental Results with Tree Adjunct Grammar Guided Genetic Programming
EuroGP '02 Proceedings of the 5th European Conference on Genetic Programming
A hybrid heuristic-genetic algorithm for task scheduling in heterogeneous processor networks
Journal of Parallel and Distributed Computing
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Grammatical Evolution (GE) is a grammar-based GA which generates computer programs. GE has the distinction that its input is a BNF, which permits it to generate programs in any language, of arbitrary complexity. Part of the power of GE is that it is closer to natural DNA than other Evolutionary Algorithms, and thus can benefit from natural phenomena such as a separation of search and solution spaces through a genotype to phenotype mapping, and a genetic code degeneracy which can give rise to silent mutations that have no effect on the phenotype. It has previously been shown how runs of GE cire competitive with GP, and in this paper we analyse the feature of genetic code degeneracy, and its implications for genotypic diversity. Results show that genetic diversity is improved as a result of degeneracy in the genetic code for the problem domains addressed here.