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Grammatical Evolution

  • Michael O’Neil
  • Conor Ryan
Part of the Genetic Programming Series book series (GPEM, volume 4)

Abstract

This chapter describes Grammatical Evolution (GE) in detail (Ryan et al., 1998; O’Neill and Ryan, 2001; O’Neill, 2001). We show that it is an evolutionary algorithm (EA) that can evolve complete programs in an arbitrary language using a variable-length binary string. The binary genome determines which production rules in a Backus Naur Form (BNF) grammar definition are used in a genotype-to-phenotype mapping process to a program. GE is set up such that the evolutionary algorithm is independent of the output programs by virtue of the genotype-phenotype mapping, allowing GE to take advantage of advances in EA research. The BNF grammar, like the EA, is a plug-in component of the system that determines the syntax and language of the output code, hence, it is possible to evolve programs in an arbitrary language.

Keywords

Genetic Programming Genetic Code Mapping Process Production Rule Binary String 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2003

Authors and Affiliations

  • Michael O’Neil
    • 1
  • Conor Ryan
    • 1
  1. 1.University of LimerickIreland

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