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Intelligent Systems

A Modern Approach

  • Crina Grosan
  • Ajith Abraham

Part of the Intelligent Systems Reference Library book series (ISRL, volume 17)

Table of contents

  1. Front Matter
  2. Crina Grosan, Ajith Abraham
    Pages 1-11
  3. Crina Grosan, Ajith Abraham
    Pages 13-52
  4. Crina Grosan, Ajith Abraham
    Pages 53-81
  5. Crina Grosan, Ajith Abraham
    Pages 83-109
  6. Crina Grosan, Ajith Abraham
    Pages 111-129
  7. Crina Grosan, Ajith Abraham
    Pages 131-147
  8. Crina Grosan, Ajith Abraham
    Pages 149-185
  9. Crina Grosan, Ajith Abraham
    Pages 187-217
  10. Crina Grosan, Ajith Abraham
    Pages 219-260
  11. Crina Grosan, Ajith Abraham
    Pages 261-268
  12. Crina Grosan, Ajith Abraham
    Pages 269-280
  13. Crina Grosan, Ajith Abraham
    Pages 281-323
  14. Crina Grosan, Ajith Abraham
    Pages 325-344
  15. Crina Grosan, Ajith Abraham
    Pages 345-386
  16. Crina Grosan, Ajith Abraham
    Pages 387-407
  17. Crina Grosan, Ajith Abraham
    Pages 409-422
  18. Crina Grosan, Ajith Abraham
    Pages 423-450

About this book

Introduction

Computational intelligence is a well-established paradigm, where new theories with a sound biological understanding have been evolving. The current experimental systems have many of the characteristics of biological computers (brains in other words) and are beginning to be built to perform a variety of tasks that are difficult or impossible to do with conventional computers. As evident, the ultimate achievement in this field would be to mimic or exceed human cognitive capabilities including reasoning, recognition, creativity, emotions, understanding, learning and so on. This book comprising of 17 chapters offers a step-by-step introduction (in a chronological order) to the various modern computational intelligence tools used in practical problem solving. Staring with different search techniques including informed and uninformed search, heuristic search, minmax, alpha-beta pruning methods, evolutionary algorithms and swarm intelligent techniques; the authors illustrate the design of knowledge-based systems and advanced expert systems, which incorporate uncertainty and fuzziness. Machine learning algorithms including decision trees and artificial neural networks are presented and finally the fundamentals of hybrid intelligent systems are also depicted.

 

Academics, scientists as well as engineers engaged in research, development and application of computational intelligence techniques, machine learning and data mining would find the comprehensive coverage of this book invaluable.

Keywords

Computational Intelligence Evolutionary Computation Machine Learning Neural Networks

Authors and affiliations

  • Crina Grosan
    • 1
  • Ajith Abraham
    • 2
  1. 1.Department of Computer Science, Faculty of Mathematics and Computer ScienceBabes-Bolyai UniversityCluj - NapocaRomania
  2. 2.Machine Intelligence Research Labs (MIR Labs)Scientific Network for Innovation and Research ExcellenceAuburnUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-642-21004-4
  • Copyright Information Springer-Verlag Berlin Heidelberg 2011
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-642-21003-7
  • Online ISBN 978-3-642-21004-4
  • Series Print ISSN 1868-4394
  • Series Online ISSN 1868-4408
  • Buy this book on publisher's site