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Efficient Crossover in the GAuGE System

  • Miguel Nicolau
  • Conor Ryan
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3003)

Abstract

This paper presents a series of context-preserving crossover operators for the GAuGE system. These operators have been designed to respect the representation of genotype strings in GAuGE, thereby making sensible changes at the genotypic level. Results on a set of problems suggest that some of these operators can improve the maintenance and propagation of building blocks in GAuGE, as well as its scalability, and could be of use to other systems using structural evolving genomes.

Keywords

Genetic Algorithm Mapping Process Crossover Operator Crossover Point 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-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Miguel Nicolau
    • 1
  • Conor Ryan
    • 1
  1. 1.Biocomputing and Developmental Systems Group Computer Science and Information Systems DepartmentUniversity of LimerickIreland

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