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Introduction to Computational Intelligence Paradigms

  • Z. Chen
  • A. M. Fanelli
  • G. Castellano
  • L. C. Jain
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 62)

Abstract

Computational intelligence techniques involve the use of computers to enable machines to simulate human performance. The prominent paradigms used include AI systems, artificial neural networks, multimedia, fuzzy logic, evolutionary computing techniques, artificial life, computer vision, adaptive intelligence, and chaos engineering. These knowledge-based computational intelligence techniques have generated tremendous interest among scientists and application engineers due to a number of benefits such as generalization, adaptation, fault tolerance and self-repair, self-organization and evolution. Successful demonstration of the applications of knowledge-based systems theories will aid scientists and engineers in finding sophisticated and low cost solutions to difficult problems. This chapter provides a simple introduction to computational intelligence paradigms.

Keywords

Genetic Algorithm Fuzzy Logic Input Pattern Fuzzy Logic Controller Predicate Logic 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Physica-Verlag Heidelberg 2001

Authors and Affiliations

  • Z. Chen
  • A. M. Fanelli
  • G. Castellano
  • L. C. Jain

There are no affiliations available

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