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A New, Node-Focused Model for Genetic Programming

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Book cover Genetic Programming (EuroGP 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7244))

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Abstract

We introduce Single Node Genetic Programming (SNGP), a new graph-based model for genetic programming in which every individual in the population consists of a single program node. Function operands are other individuals, meaning that the graph structure is imposed externally on the population as a whole, rather than existing within its members. Evolution is via a hill-climbing mechanism using a single reversible operator. Experimental results indicate substantial improvements over conventional GP in terms of solution rates, efficiency and program sizes.

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Author information

Authors and Affiliations

  1. Department 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. School of Computer Science, University of Birmingham, B15 2TT, Edgbaston, Birmingham, UK

    Alberto Moraglio

  2. INESC-ID Lisboa, Rua Alves Redol 9, 1000-029, Lisboa, Portugal

    Sara Silva

  3. Institute of Computing Science, Poznań University of Technology, Piotrowo 2, 60-965, Poznań, Poland

    Krzysztof Krawiec

  4. Faculty of Sciences and Technology, Department of Informatics Engineering, University of Coimbra, Pólo II - Pinhal de Marrocos, 3030, Coimbra, Portugal

    Penousal Machado

  5. ETSI Informática, Universidad de Málaga, Campus de Teatinos, 29071, Málaga, Spain

    Carlos Cotta

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© 2012 Springer-Verlag Berlin Heidelberg

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Jackson, D. (2012). A New, Node-Focused Model for Genetic Programming. In: Moraglio, A., Silva, S., Krawiec, K., Machado, P., Cotta, C. (eds) Genetic Programming. EuroGP 2012. Lecture Notes in Computer Science, vol 7244. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29139-5_5

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  • DOI: https://doi.org/10.1007/978-3-642-29139-5_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29138-8

  • Online ISBN: 978-3-642-29139-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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