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Introducing a Perl Genetic Programming System - and Can Meta-evolution Solve the Bloat Problem?

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Book cover Genetic Programming (EuroGP 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2610))

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Abstract

An open source Perl package for genetic programming, called PerlGP, is presented. The supplied algorithm is strongly typed tree-based GP with homologous crossover. User-defined grammars allow any valid Perl to be evolved, including object oriented code and parameters of the PerlGP system itself. Time trials indicate that PerlGP is around 10 times slower than a C based system on a numerical problem, but this is compensated by the speed and ease of implementing new problems, particularly string-based ones. The effect of per-node, fixed and self-adapting crossover and mutation rates on code growth and fitness is studied. On a pi estimation problem, self-adapting rates give both optimal and compact solutions. The source code and manual can be found at http://perlgp.org.

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Author information

Authors and Affiliations

  1. Stockholm Bioinformatics Center, Stockholm University, 106 91, Stockholm, Sweden

    Robert M. MacCallum

Authors
  1. Robert M. MacCallum
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Editor information

Editors and Affiliations

  1. Computer Science and Information Systems, University of Limerick, Limerick, Ireland

    Conor Ryan

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

    Terence Soule

  3. Department of Computer Science, Free University of Amsterdam, 1081, HV Amsterdam, The Netherlands

    Maarten Keijzer

  4. Department of Computer Science, University of Essex, Wivenhoe Park, CO4 3SQ, Colchester, UK

    Edward Tsang  & Riccardo Poli  & 

  5. Department of Computer Science, University of Coimbra, Polo II, Pinhal Marrocos, 3030-290, Coimbra, Portugal

    Ernesto Costa

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© 2003 Springer-Verlag Berlin Heidelberg

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MacCallum, R.M. (2003). Introducing a Perl Genetic Programming System - and Can Meta-evolution Solve the Bloat Problem?. In: Ryan, C., Soule, T., Keijzer, M., Tsang, E., Poli, R., Costa, E. (eds) Genetic Programming. EuroGP 2003. Lecture Notes in Computer Science, vol 2610. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36599-0_34

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  • DOI: https://doi.org/10.1007/3-540-36599-0_34

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-00971-9

  • Online ISBN: 978-3-540-36599-0

  • eBook Packages: Springer Book Archive

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