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Single Node Genetic Programming on Problems with Side Effects

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Book cover Parallel Problem Solving from Nature - PPSN XII (PPSN 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7491))

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Abstract

Single Node Genetic Programming (SNGP) offers a new approach to GP in which every member of the population consists of just a single program node. Operands are formed from other members of the population, and evolution is driven by a hill-climbing approach using a single reversible operator. When the functions being used in the problem are free from side effects, it is possible to make use of a form of dynamic programming, which provides huge efficiency gains. In this research we turn our attention to the use of SNGP when the solution of problems relies on the presence of side effects. We demonstrate that SNGP can still be superior to conventional GP, and examine the role of evolutionary strategies in achieving this.

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Authors and Affiliations

  1. Dept. of Computer Science, University of Liverpool, Liverpool, L69 3BX, United Kingdom

    David Jackson

Authors
  1. David Jackson
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Editor information

Editors and Affiliations

  1. Centro de Investigacion y de Estudios, Avanzados del Instituto Politecnico Nacional (CINVESTAV-IPN), Departmento de Computation, Av. IPN No. 2508, Col. San Pedro Zacatenco, 0360, Mexico, D.F., Mexico

    Carlos A. Coello Coello

  2. Department of Mathematics and Computer Science, University of Catania, V.le A. Doria 6, 95125, Catania, Italy

    Vincenzo Cutello  & Mario Pavone  & 

  3. Kanpur Genetic Algorithms Laboratory (KanGAL), Indian Institute of Technology, Kanpur, Kanpur, India

    Kalyanmoy Deb

  4. Department of Computer Science, University of New, Mexico, USA

    Stephanie Forrest

  5. Department of Mathematics and Computer Science, University of Catania, Viale A. Doria 6, 95125, Catania, Italy

    Giuseppe Nicosia

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© 2012 Springer-Verlag Berlin Heidelberg

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Jackson, D. (2012). Single Node Genetic Programming on Problems with Side Effects. In: Coello, C.A.C., Cutello, V., Deb, K., Forrest, S., Nicosia, G., Pavone, M. (eds) Parallel Problem Solving from Nature - PPSN XII. PPSN 2012. Lecture Notes in Computer Science, vol 7491. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32937-1_33

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  • DOI: https://doi.org/10.1007/978-3-642-32937-1_33

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32936-4

  • Online ISBN: 978-3-642-32937-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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