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Learning Recursive Functions with Object Oriented Genetic Programming

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Genetic Programming (EuroGP 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3905))

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Abstract

This paper describes the evolution of recursive functions within an Object-Oriented Genetic Programming (OOGP) system. We evolved general solutions to factorial, Fibonacci, exponentiation, even-n-Parity, and nth-3. We report the computational effort required to evolve these methods and provide a comparison between crossover and mutation variation operators, and also undirected random search. We found that the evolutionary algorithms performed much better than undirected random search, and thats mutation outperformed crossover on most problems.

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Authors and Affiliations

  1. Department of Computer Science, University of Essex, Colchester, CO4 3SQ, UK

    Alexandros Agapitos & Simon M. Lucas

Authors
  1. Alexandros Agapitos
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  2. Simon M. Lucas
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Editor information

Editors and Affiliations

  1. Université Louis Pasteur, LSIIT, FDBT, Pôle API,, F-67400, Illkirch, France

    Pierre Collet

  2. Institut des Systèmes d’Information (ISI), Université de Lausanne, Hautes Etudes Commerciales (HEC),, Switzerland

    Marco Tomassini

  3. Lehrstuhl für Informatik II, Universität Würzburg, Am Hubland,, 97074, Würzburg, Germany

    Marc Ebner

  4. GE Global Research, Niskayuna,, NY, USA

    Steven Gustafson

  5. Aston University, Birmingham, UK

    Anikó Ekárt

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© 2006 Springer-Verlag Berlin Heidelberg

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Agapitos, A., Lucas, S.M. (2006). Learning Recursive Functions with Object Oriented Genetic Programming. In: Collet, P., Tomassini, M., Ebner, M., Gustafson, S., Ekárt, A. (eds) Genetic Programming. EuroGP 2006. Lecture Notes in Computer Science, vol 3905. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11729976_15

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  • DOI: https://doi.org/10.1007/11729976_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-33143-8

  • Online ISBN: 978-3-540-33144-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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