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Efficient Crossover in the GAuGE System

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Book cover Genetic Programming (EuroGP 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3003))

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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.

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Author information

Authors and Affiliations

  1. Biocomputing and Developmental Systems Group Computer Science and Information Systems Department, University of Limerick, Ireland

    Miguel Nicolau & Conor Ryan

Authors
  1. Miguel Nicolau
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  2. Conor Ryan
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Editor information

Editors and Affiliations

  1. No Affiliation,  

    Maarten Keijzer

  2. Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 02139, Cambridge, MA, USA

    Una-May O’Reilly

  3. University of Essex Department of Computing and Electronic Systems, Wivenhoe Park, CO4 3SQ, Colchester, UK

    Simon Lucas

  4. Centre of Informatics and Systems of the University of Coimbra,  

    Ernesto Costa

  5. Department of Computer Science, University of Idaho, ID 83844-1010, Moscow,  

    Terence Soule

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© 2004 Springer-Verlag Berlin Heidelberg

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Nicolau, M., Ryan, C. (2004). Efficient Crossover in the GAuGE System. In: Keijzer, M., O’Reilly, UM., Lucas, S., Costa, E., Soule, T. (eds) Genetic Programming. EuroGP 2004. Lecture Notes in Computer Science, vol 3003. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24650-3_12

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  • DOI: https://doi.org/10.1007/978-3-540-24650-3_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-21346-8

  • Online ISBN: 978-3-540-24650-3

  • eBook Packages: Springer Book Archive

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