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Computer Science - Artificial Intelligence | Computational Intelligence - A Methodological Introduction

Computational Intelligence

A Methodological Introduction

Kruse, R., Borgelt, C., Klawonn, F., Moewes, C., Steinbrecher, M., Held, P.

2013, XI, 488 p. 234 illus.

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  • Written by a team of highly-regarded experts, with extensive experience in both academia and industry
  • Offers a profound theoretical introduction to computational intelligence for both students and practitioners
  • Provides electronic supplementary material at an associated website, including module descriptions, lecture slides, exercises with solutions, and software tools

Computational intelligence (CI) encompasses a range of nature-inspired methods that exhibit intelligent behavior in complex environments.

This clearly-structured, classroom-tested textbook/reference presents a methodical introduction to the field of CI. Providing an authoritative insight into all that is necessary for the successful application of CI methods, the book describes fundamental concepts and their practical implementations, and explains the theoretical background underpinning proposed solutions to common problems. Only a basic knowledge of mathematics is required.

Topics and features:

  • Provides electronic supplementary material at an associated website, including module descriptions, lecture slides, exercises with solutions, and software tools
  • Contains numerous examples and definitions throughout the text
  • Presents self-contained discussions on artificial neural networks, evolutionary algorithms, fuzzy systems and Bayesian networks
  • Covers the latest approaches, including ant colony optimization and probabilistic graphical models
  • Written by a team of highly-regarded experts in CI, with extensive experience in both academia and industry

Students of computer science will find the text a must-read reference for courses on artificial intelligence and intelligent systems. The book is also an ideal self-study resource for researchers and practitioners involved in all areas of CI.

Content Level » Graduate

Keywords » Artificial Neural Networks - Bayesian Networks - Computational Intelligence - Evolutionary Algorithms - Fuzzy Systems

Related subjects » Artificial Intelligence - Computational Intelligence and Complexity

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