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Chaos Theory for Evolutionary Algorithms Researchers

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Evolutionary Algorithms and Chaotic Systems

Part of the book series: Studies in Computational Intelligence ((SCI,volume 267))

Abstract

This chapter deals with chaotic systems. Based on the characterization of deterministic chaos, universal features of that kind of behavior are explained. It is shown that despite the deterministic nature of chaos, long term behavior is unpredictable. This is called sensitivity to initial conditions. We further give a concept of quantifying chaotic dynamics: the Lyapunov exponent. Moreover, we explain how chaos can originate from order by period doubling, intermittence, chaotic transients and crises. In the second part of the chapter we discuss different examples of systems showing chaos, for instance mechanical, electronic, biological, meteorological, algorithmical and astronomical systems.

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Author information

Authors and Affiliations

  1. Institute of Information Theory and Automation, Academy of Sciences of the Czech Republic, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic

    Sergej Celikovsky

  2. Faculty of Applied Informatics, Tomas Bata University in Zlin, Nad Stranemi 4511, Zlin, 76001, Czech Republic

    Ivan Zelinka

  3. Faculty of Electrical Engineering and Computer Science, VSB-TUO, 17. listopadu 15, 708 33, Ostrava-Poruba, Czech Republic

    Ivan Zelinka

Authors
  1. Sergej Celikovsky
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  2. Ivan Zelinka
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Editor information

Editors and Affiliations

  1. Department of Applied Informatics Faculty of Applied Informatics, Tomas Bata Univerzity in Zlin, Nad Stranemi 4511, Zlin, 76001, Czech Republic

    Ivan Zelinka

  2. Department of Control Engineering Faculty of Electrical Engineering, Czech Technical University in Prague UTIA AV CR, Pod vodarenskou vezi 4, 182 08, Prague 8, Czech Republic

    Sergej Celikovsky

  3. Faculty of Electrical Engineering & Information Technology, HTWK Leipzig, 04251, Leipzig, Germany

    Hendrik Richter

  4. Department of Electronic Engineering, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong SAR P. R. China

    Guanrong Chen

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Celikovsky, S., Zelinka, I. (2010). Chaos Theory for Evolutionary Algorithms Researchers. In: Zelinka, I., Celikovsky, S., Richter, H., Chen, G. (eds) Evolutionary Algorithms and Chaotic Systems. Studies in Computational Intelligence, vol 267. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10707-8_3

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  • DOI: https://doi.org/10.1007/978-3-642-10707-8_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-10706-1

  • Online ISBN: 978-3-642-10707-8

  • eBook Packages: EngineeringEngineering (R0)

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