Russ Eberhart and Yuhui Shi have succeeded in integrating various
natural and engineering disciplines to establish Computational
Intelligence. This is the first comprehensive textbook, including
lots of practical examples. -Shun-ichi Amari, RIKEN Brain Science
Institute, Japan
This book is an excellent choice on its own, but, as in my case,
will form the foundation for our advanced graduate courses in the
CI disciplines. -James M. Keller, University of Missouri-Columbia
The excellent new book by Eberhart and Shi asserts that
computational intelligence rests on a foundation of evolutionary
computation. This refreshing view has set the book apart from other
books on computational intelligence. The book has an emphasis on
practical applications and computational tools, which are very
useful and important for further development of the computational
intelligence field. -Xin Yao, The Centre of Excellence for Research
in Computational Intelligence and Applications, Birmingham
The "soft" analytic tools that comprise the field of computational
intelligence have matured to the extent that they can, often in
powerful combination with one another, form the foundation for a
variety of solutions suitable for use by domain experts without
extensive programming experience.
Computational Intelligence: Concepts to Implementations provides
the conceptual and practical knowledge necessary to develop
solutions of this kind. Focusing on evolutionary computation,
neural networks, and fuzzy logic, the authors have constructed an
approach to thinking about and working with computational
intelligence that has, in their extensive experience, proved highly
effective.
Features
- Movesclearly and efficiently from concepts and paradigms to
algorithms and implementation techniques by focusing, in the early
chapters, on the specific concepts and paradigms that inform the
authors' methodologies.
- Explores a number of key themes, including self-organization,
complex adaptive systems, and emergent computation.
- Details the metrics and analytical tools needed to assess the
performance of computational intelligence tools.
- Concludes with a series of case studies that illustrate a wide
range of successful applications.
- Presents code examples in C and C++.
- Provides, at the end of each chapter, review questions and
exercises suitable for graduate students, as well as researchers
and practitioners engaged in self-study.
- Makes available, on a companion website, a number of software
implementations that can be adapted for real-world applications.
- Moves clearly and efficiently from concepts and paradigms to
algorithms and implementation techniques by focusing, in the early
chapters, on the specific concepts and paradigms that inform the
authors' methodologies.
- Explores a number of key themes, including self-organization,
complex adaptive systems, and emergent computation.
- Details the metrics and analytical tools needed to assess the
performance of computational intelligence tools.
- Concludes with a series of case studies that illustrate a wide
range of successful applications.
- Presents code examples in C and C++.
- Provides, at the end of each chapter, review questions and
exercises suitable for graduate students, as well as researchers
and practitioners engaged in self-study.
- Makes available, on a companionwebsite, a number of software
implementations that can be adapted for real-world applications.
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