Artificial Intelligence: A Guide To Intelligent Systems, 3rd edition

Published by Addison-Wesley (November 9, 2011) © 2012

  • Michael Negnevitsky School of Electrical Engineering and Computer Science, University of Tasmania
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An introductory text suitable for a one-semester course

Negnevitsky shows students how to build intelligent systems drawing on techniques from knowledge-based systems, neural networks, fuzzy systems, evolutionary computation and now also intelligent agents. The principles behind these techniques are explained without resorting to complex mathematics, showing how the various techniques are implemented, when they are useful and when they are not. No particular programming language is assumed and the book does not tie itself to any of the software tools available.

  • Introduction to knowledge based intelligent systems
  • Rule-based expert systems
  • Uncertainty management in rule-based expert systems
  • Fuzzy expert systems
  • Frame-based expert systems
  • Artificial neural networks
  • Evolutionary computation
  • Hybrid intelligent systems
  • Knowledge engineering
  • Data mining and knowledge discovery
  • Glossary
  • Appendix: AI tools and vendors

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