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O'Neill, M. and Ryan, C. (1999) Genetic Code Degeneracy: Implications for Grammatical Evolution and Beyond. In D. Floreano and J. Nicoud and F. Mondada, editors, ECAL99, pages 149--153. Berlin: Springer-Verlag.
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Genetic Code Degeneracy: Implications for
Grammatical Evolution and Beyond
Michael O'Neill & Conor Ryan
Dept. of Computer Science and Information Systems
University of Limerick
Ireland
fMichael.ONeilljConor.Ryang@ul.ie
Abstract. Grammatical Evolution (GE) is a grammar­based 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 are 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.
1 Introduction Grammatical Evolution (GE) is a grammar­based, variable length, linear genome system which is capable of generating programs or expressions in any language. Rather than the functions and terminals associated with GP [3], GE takes a BNF specification of a language, or subset thereof, from which it can subsequently generate compilable code. The BNF is used to build a program by applying production rules to elements of the non­terminal set of the BNF definition, in a mapping process to generate the output code from a simple binary string. GE has been successfully applied to a number of diverse problem domains such as, symbolic regression [9], finding trigonometric identities [10], symbolic integration [10], and the Santa Fe trail [7]. The results compared favorably with systems such as GP, and has been shown to outperform GP [7]. In the spirit of Artificial Life, one ...
BibTex
@inproceedings{oneill99geneticCode,
  author={Michael O'Neill and Conor Ryan},
  title={Genetic Code Degeneracy: Implications for Grammatical Evolution and Beyond},
  year={1999},
  pages={149-153},
  address={Berlin},
  editor={D. Floreano and J. Nicoud and F. Mondada},
  publisher={Springer-Verlag},
  booktitle={ECAL99},
  url={http://www.isrl.uiuc.edu/~amag/langev/paper/oneill99geneticCode.html}
}

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