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Saving Effort in Parallel GP by Means of Plagues

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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

Recently, a new technique that allows Genetic Programming to save computing resources has been proposed. This technique was presented as a new operator acting on the population, and was called plague. By removing some individuals every generation, plague aims at compensating for the increase in size of individuals, thus saving computing time when looking for solutions. By means of some test problems, we show that the technique is also useful when employing a parallel version of GP, such as that based on the island model.

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Authors and Affiliations

  1. Artificial Evolution Group, Centro Universitario de Mérida, C/Sta Teresa de Jornet, 38, 0688, Mérida, SPAIN

    F. Fernández & A. Martín

Authors
  1. F. Fernández
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  2. A. Martín
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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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Fernández, F., Martín, A. (2004). Saving Effort in Parallel GP by Means of Plagues. 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_25

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  • DOI: https://doi.org/10.1007/978-3-540-24650-3_25

  • 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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