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Transgenic Evolution for Classification Tasks with HERCL

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Artificial Life and Computational Intelligence (ACALCI 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8955))

Abstract

We explore the evolution of programs for classification tasks, using the recently introduced Hierarchical Evolutionary Re-Combination Language (HERCL) which has been designed as an austere and general-purpose language, with a view toward modular evolutionary computation, combining elements from Linear GP with stack-based operations from forth. We show that evolved HERCL programs can successfully learn to perform a variety of benchmark classification tasks, and that performance is enhanced by the sharing of genetic material between tasks.

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Author information

Authors and Affiliations

  1. School of Computer Science and Engineering, University of New South Wales, Sydney, 2052, Australia

    Alan D. Blair

Authors
  1. Alan D. Blair
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Editor information

Editors and Affiliations

  1. School of Electrical Engineering and Computer Science, The University of Newcastle, 2308, Callaghan, NSW, Australia

    Stephan K. Chalup

  2. School of Computer Science and Engineering, The University of New South Wales, 2052, Sydney, NSW, Australia

    Alan D. Blair

  3. Faculty of Business, Bond University, 4226, Robina, QLD, Australia

    Marcus Randall

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Blair, A.D. (2015). Transgenic Evolution for Classification Tasks with HERCL . In: Chalup, S.K., Blair, A.D., Randall, M. (eds) Artificial Life and Computational Intelligence. ACALCI 2015. Lecture Notes in Computer Science(), vol 8955. Springer, Cham. https://doi.org/10.1007/978-3-319-14803-8_15

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  • DOI: https://doi.org/10.1007/978-3-319-14803-8_15

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-14802-1

  • Online ISBN: 978-3-319-14803-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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