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Evolutionary Algorithms with Stable Mutations Based on a Discrete Spectral Measure

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Artifical Intelligence and Soft Computing (ICAISC 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6114))

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Abstract

In this paper the concept of multidimensional discrete spectral measure is introduced in the context of its application to real-valued evolutionary algorithms. The notion of discrete spectral measure makes possible to uniquely define a class of multivariate heavy-tailed distributions, that have received more and more attention of evolutionary optimization commynity , recently. Simple sample illustrates advantages of such approach.

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Author information

Authors and Affiliations

  1. Institute of Control and Computation Engineering, University of Zielona Góra, ul. Podgórna 50, 65–246, Zielona Góra, Poland

    Andrzej Obuchowicz & Przemysław Prȩtki

Authors
  1. Andrzej Obuchowicz
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  2. Przemysław Prȩtki
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Editor information

Editors and Affiliations

  1. Department of Artificial Intelligence, Academy of Humanities and Economics, Poland

    Leszek Rutkowski

  2. Academy of Humanities and Economics in Łódź, ul. Rewolucji 1905 nr 64, Łódź, Poland

    Rafał Scherer

  3. Institute of Automatics, AGH University of Science and Technology, Al. Mickiewicza 30, PL-30-059, Kraków, Poland

    Ryszard Tadeusiewicz

  4. Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley Initiative in Soft Computing (BISC), 94720-1776, CA

    Lotfi A. Zadeh

  5. Computational Intelligence Laboratory Department of Electrical and Computer Engineering, University of Louisville, 40292, Louisville, KY

    Jacek M. Zurada

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© 2010 Springer-Verlag Berlin Heidelberg

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Obuchowicz, A., Prȩtki, P. (2010). Evolutionary Algorithms with Stable Mutations Based on a Discrete Spectral Measure. In: Rutkowski, L., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artifical Intelligence and Soft Computing. ICAISC 2010. Lecture Notes in Computer Science(), vol 6114. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13232-2_22

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  • DOI: https://doi.org/10.1007/978-3-642-13232-2_22

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-13231-5

  • Online ISBN: 978-3-642-13232-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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