AI Intelligent System Guide (English Version · 2nd Edition)

Author: Negnevitsky
Publisher:
Publish Date: 2005-04-01
Features: Artificial intelligence is often considered a highly complex and even intimidating discipline in computer science. For a long time, books on artificial intelligence have often included complex matrix algebra and differential equations. This book was developed from the author's lecture notes used for many years while teaching students with little knowledge of calculus. It assumes that readers have no prior programming experience and explains that most of the fundamental knowledge in intelligent systems is actually simple and easy to understand. The book has currently been adopted by several universities internationally (e.g., University of Magdeburg in Germany, Hiroshima University in Japan, Boston University and Rochester Institute of Technology in the U.S.). If you are looking for an accessible and easy-to-understand introductory textbook for courses on artificial intelligence or intelligent system design, or if you are not a professional in the field of computer science but are seeking a self-study guide to introduce the new developments in knowledge-based systems, this book is the ideal choice. The main content of the book: Rule-based expert systems, fuzzy expert systems, frame-based expert systems, artificial neural networks, evolutionary computation, hybrid intelligent systems, knowledge engineering, data mining.