Computational Intelligence

Concepts to Implementations

Russell C. Eberhart, Yuhui Shi

• Publisher: Morgan Kaufmann
• Year: 2011
• ISBN:
  9780080553832
• Topic: Computer Science
• Subtopic: Artificial Intelligence (AI) & Semantics
• Index: Computer Science

Computational Intelligence: Concepts to Implementations provides the most complete and practical coverage of computational intelligence tools and techniques to date. This book integrates various natural and engineering disciplines to establish Computational Intelligence. This is the first comprehensive textbook on the subject, supported with lots of practical examples. It 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.

This book lays emphasis on practical applications and computational tools, which are very useful and important for further development of the computational intelligence field. 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. The book moves clearly and efficiently from concepts and paradigms to algorithms and implementation techniques by focusing, in the early chapters, on the specific con. It explores a number of key themes, including self-organization, complex adaptive systems, and emergent computation. It details the metrics and analytical tools needed to assess the performance of computational intelligence tools. The book concludes with a series of case studies that illustrate a wide range of successful applications.

This book will appeal to professional and academic researchers in computational intelligence applications, tool development, and systems.

• 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

Table of contents

• Front Cover
• Computational Intelligence
• Copyright Page
• Table of Contents
• Preface
• Chapter 1. Foundations
• Chapter 2. Computational Intelligence
• Chapter 3. Evolutionary Computation Concepts and Paradigms
• Chapter 4. Evolutionary Computation Implementations
• Chapter 5. Neural Network Concepts and Paradigms
• Chapter 6. Neural Network Implementations
• Chapter 7. Fuzzy Systems Conceptsand Paradigms
• Chapter 8. Fuzzy Systems Implementations
• Chapter 9. Computational Intelligence Implementations
• Chapter 10. Performance Metrics
• Chapter 11. Analysis and Explanation
• Bibliography
• Index
• About the Authors
• Chapter 12. Case Study Summaries
• Summary
• Exercises
• Glossary