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Dynamic Trait Expression for Multiploid Individuals of Evolutionary Algorithms

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Engineering of Intelligent Systems (IEA/AIE 2001)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2070))

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Abstract

The use of multiploid structures for individuals in evolutionary algorithms has been shown to have the advantage of including redundant information, increasing population diversity and in some cases improving non- stationary function optimisation performance. These advantages can translate into improved avoidance of premature convergence and an ability to cope with complex problems. However, as multiple information for the same trait is available, a method of gene selection or activation is required. This paper describes a dynamic decision method for gene selection, presents proof of concept results for this type of structure and outlines proposed benefits and applications.

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Authors and Affiliations

  1. Centre for Intelligent Systems and Complex Processes, School of Biophysical Science and Electrical Engineering Swinburne University of Technology, Victoria, 3122, Australia

    Clinton Woodward & Tim Hendtlass

Authors
  1. Clinton Woodward
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  2. Tim Hendtlass
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Editor information

Editors and Affiliations

  1. Hungarian Academy of Sciences, Intelligent Manufacturing and Business Processes Computer and Automation Research Institute, Kende utca 13-17, 1111, Budapest, Hungary

    László Monostori  & József Váncza  & 

  2. Department of Computer Science 601 University Drive, Southwest Texas State University, San Marcos, TX, 78666-4616, USA

    Moonis Ali

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© 2001 Springer-Verlag Berlin Heidelberg

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Woodward, C., Hendtlass, T. (2001). Dynamic Trait Expression for Multiploid Individuals of Evolutionary Algorithms. In: Monostori, L., Váncza, J., Ali, M. (eds) Engineering of Intelligent Systems. IEA/AIE 2001. Lecture Notes in Computer Science(), vol 2070. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45517-5_42

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  • DOI: https://doi.org/10.1007/3-540-45517-5_42

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42219-8

  • Online ISBN: 978-3-540-45517-2

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