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Transposon element technique applied to GA-based John Muir's trail test

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High-Performance Computing and Networking (HPCN-Europe 1998)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1401))

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Abstract

We develop a new adaptive learning evolutionary algorithm - parallel transposon element technique (PTET). This algorithm is based on invasion of evolving genomes by parasitic/selfish mobile genetic elements. PTET uses island model, where multiple independent subpopulations each run a steady-state genetic algorithm (GA) on different processors and occasionally fit strings migrate between the subpopulations. We studied the efficiency of new technique on classical test problem - the John Muir Ant's Trail experiment. This problem is a behaviour algorithm and can be tested both for smooth and rugged and/or multiply connected fitness landscapes.

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Authors and Affiliations

  1. Institute for High-Performance Computing and Data Bases, Fontanka emb. 120, office 7, 198005, St.Petersburg, Russia

    A. V. Spirov & A. S. Kadyrov

Authors
  1. A. V. Spirov
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  2. A. S. Kadyrov
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Peter Sloot Marian Bubak Bob Hertzberger

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© 1998 Springer-Verlag Berlin Heidelberg

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Spirov, A.V., Kadyrov, A.S. (1998). Transposon element technique applied to GA-based John Muir's trail test. In: Sloot, P., Bubak, M., Hertzberger, B. (eds) High-Performance Computing and Networking. HPCN-Europe 1998. Lecture Notes in Computer Science, vol 1401. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0037235

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  • DOI: https://doi.org/10.1007/BFb0037235

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-64443-9

  • Online ISBN: 978-3-540-69783-1

  • eBook Packages: Springer Book Archive

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