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An Introduction to Computational Intelligence Paradigms

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Practical Applications of Computational Intelligence Techniques

Part of the book series: International Series in Intelligent Technologies ((ISIT,volume 16))

Abstract

In the past decade, Artificial Intelligence (AI) had a grand paradigm shift from its domain of symbolic to non-symbolic and numeric computation. Prior to the mid-eighties, symbolic logic was used as the unique tool in the development of algorithms for the classical AI problems like reasoning, planning, and machine learning. The incompleteness of the traditional AI was shortly realized, but unfortunately no handy solutions were readily available at the time. In the nineties the monumental developments in fuzzy logic, artificial neural nets, genetic algorithms and probabilistic reasoning models motivated the researchers around the world to explore the possibilities of building more humanlike machines using these new tools. Consequently, a large number of intelligent systems that can complement the behavior of the traditional symbol-processing machines were built by employing these tools. This chapter provides a brief overview on the fundamental AI tools and their synergism, which together is informally known as computational intelligence.

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Authors
  1. A. Konar
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  2. L. C. Jain
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Editor information

Editors and Affiliations

  1. University of South Australia, Adelaide, Australia

    Lakhmi Jain

  2. University of London, London, UK

    Philippe De Wilde

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Konar, A., Jain, L.C. (2001). An Introduction to Computational Intelligence Paradigms. In: Jain, L., De Wilde, P. (eds) Practical Applications of Computational Intelligence Techniques. International Series in Intelligent Technologies, vol 16. Springer, Dordrecht. https://doi.org/10.1007/978-94-010-0678-1_1

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  • DOI: https://doi.org/10.1007/978-94-010-0678-1_1

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-010-3868-3

  • Online ISBN: 978-94-010-0678-1

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