Artificial Intelligence: A Guide to Intelligent Systems

by Michael Negnevitsky

Book Overview

This title shows students how to build intelligent systems drawing on techniques from knowledge-based systems, neural networks, fuzzy systems, evolutionary computation and now also intelligent agents.... This description may be from another edition of this product.

• Format: Hardcover
• Language: English
• ISBN: 0321204662
• ISBN13: 9780321204660
• Release Date: November 2004
• Publisher: Addison-Wesley Professional
• Length: 415 Pages
• Weight: 1.75 lbs.
• Dimensions: 1.1" x 6.1" x 9.5"

Customer Reviews

explains key ideas with minimal maths complications

The field of Artificial Intelligence has been around for decades. During which there have been numerous advances and disappointments. Often, the advances have been described in other texts using highly mathematical treatments. All to the good. Except that this does tend to act as a barrier to newcomers to AI, who might not have a very strong maths background. And even for those who do, the sheer amount of maths to understand in those books can be time consuming. Which is the attraction of Negnevitsky's approach. He deliberately de-emphasises the maths. Enough is retained to give a valid treatment. But it is now far easier to understand the underlying ideas. Such as artificial neural networks. Here, I was also impressed to see him give proper prominence to John Hopfield's seminal contributions to neural network theory. More generally, the book covers well the entire breadth of AI. From fuzzy systems to genetic algorithms to rule-based systems.

A very good introductory text book for intelligent systems

The author explains various AI concepts in very simple terms and has managed to present the math behind some of the ideas in an understandable manner. The treatment of various topics is intermediate though but it is a good place to start and does not leave the reader riddled with complex math equations. In-fact the author has done a great job at keeping the concepts separate from the mathematics, except for some places like neural networks where it is not possible to explain the concepts without talking about the math involved. Instead of focusing too much on a particular aspect of intelligent systems this book deals with a whole spectrum of technologies such as fuzzy systems, neural networks, hybrid systems etc. The writing style of the author is very simple and clear and it is possible to finish the entire book over a period of one semester or a little more.

Excellent Treatment of Complex Topics

What Dr. Negnevitsky states in the preface of this book, "Most of the literature on AI is expressed in the jargon of computer science, and crowded with complex matrix algebra and differential equations" is an accurate assessment of current textbooks that try to go beyond just the basics of AI. Actually, this book does contain some of the same complex material that Dr. Negnevitsky accuses others for having with one exception: He does a terrific job in simplifying the complex theories behind them. At first, when I flipped through the pages, huge equations and matrices jumped at me. My first impression was that this book was for serious computer scientists or mathematicians. I was looking for simpler material for my beginning AI students. I started reading the preface and found the argument interesting.I speed-read through the first chapter and found the history of the field presented in a concise and a very well laid out fashion. I jumped into reading the beginning of chapter 2 and I was amazed at how well Dr. Negnevitsky progressed from basic ideas to more and more complex layers. With other similar books, the reader will need many basic theory books (mathematics, basic AI...) in order to understand the topics. Dr. Negnevitsky provides all the basics necessary. This same strategy is repeated for the remaining chapters. I acquired the book and read it from beginning to end. I found the material consistently well presented. One warning: this book does get very technical and complex in many chapters. However, the material in each of those chapters is progressively laid out. Even if a reader stops in the middle of some chapters, there is still a lot to gain from the experience of reading the entire book. I highly recommend it to anyone interested in really understanding beyond just keywords and delve into the internals of AI topics.Thanks to Dr. Negnevitsky for a great book.

Great Introductory Book on Soft Computing

For a beginner that wants to know where the stories about Soft Computing really converge, this book is a starting point. The style of the author is simple and great. My interest was to get a book that keeps the daunting mathematical jargons in Fuzzy Logic (contained in several other books) minimal, while presenting the concepts. I fell in love with this book, that I had to run through all the pages as if it's a novel. This book really demonstrates that the whole idea behind intelligent systems are simple and straightforward. You do not need another teacher. He presented algorithms (e.g. back-propagation)in a very simple to understand manner. Dr. Michael Negnevitsky, the author, must be a great teacher. It's a handy and nice book. I strongly recommend it.