Artificial Intelligence: A Guide to Intelligent Systems [Hardcover]

Michael Negnevitsky (Author)

Book Description

Publication Date: September 15, 2001 | ISBN-10: 0201711591 | ISBN-13: 978-0201711592 | Edition: 1

Artificial Intelligence: A Guide to Intelligent Systems provides a practical introduction to artificial intelligence that is less mathematically rigorous than other texts on the market. Its broad coverage of expert systems, artificial neural networks, fuzzy systems and evolutionary computation shows how intelligent systems work together. Michael Negnevitsky neatly explains the principles, demonstrates how systems are built, what they are useful for and how to choose the right tool for the job. No particular programming language knowledge is assumed and mathematical prerequisites are kept to a minimum.

Editorial Reviews

From the Back Cover

Virtually all the literature on artificial intelligence is expressed in the jargon of commuter science, crowded with complex matrix algebra and differential equations. Unlike many other books on computer intelligence, this one demonstrates that most ideas behind intelligent systems are simple and straightforward. The book has evolved from lectures given to students with little knowledge of calculus, and the reader needs no prerequisites associated with knowledge of any programming language. The methods used in the book have been extensively tested through several courses given by the author.

The book provides an introduction to the field of computer intelligence, covering

• rule-based expert systems,
• fuzzy expert systems,
• frame-based expert systems,
• artificail neural networks,
• evolutionary computation,
• hybrid intelligent systems,
• knowledge engineering,
• data mining.

In a university setting the book can be used as an introductory course within computer science, information systems or engineering departments. The book is also suitable as a self-study guide for non-computer science professionals, giving access to the state of the art in knowledge-based systems and computational intelligence. Everyone who faces challenging problems and cannot solve them using traditional approaches can benefit

About the Author

Dr Michael Negnevitsky is a Professor in Electrical Engineering and Computer Science at the University of Tasmania, Australia. The book has developed from his lectures to undergraduates. Educated as an electrical engineer, Dr Negnevitsky's many interests include artificial intelligence and soft computing. His research involves the development and application of intelligent systems in electrical engineering, process control and environmental engineering. He has authored and co-authored over 300 research publications including numerous journal articles, four patents for inventions and two books. --This text refers to the Paperback edition.

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Product Details

• Hardcover: 394 pages
• Publisher: Addison Wesley; 1 edition (September 15, 2001)
• Language: English
• ISBN-10: 0201711591
• ISBN-13: 978-0201711592
• Product Dimensions: 9.3 x 6.7 x 1.1 inches
• Shipping Weight: 1.6 pounds
• Average Customer Review: 4.5 out of 5 stars  See all reviews (6 customer reviews)
• Amazon Best Sellers Rank: #1,834,800 in Books (See Top 100 in Books)

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Customer Reviews

Most Helpful Customer Reviews

16 of 17 people found the following review helpful:

5.0 out of 5 stars Excellent Treatment of Complex Topics, December 14, 2003

By 

Mario Missakian (Baltimore, MD United States) - See all my reviews

This review is from: Artificial Intelligence: A Guide to Intelligent Systems (Hardcover)

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.

13 of 14 people found the following review helpful:

5.0 out of 5 stars Great Introductory Book on Soft Computing, November 9, 2002

By 

Omolade Saliu (Calgary, Canada) - See all my reviews

This review is from: Artificial Intelligence: A Guide to Intelligent Systems (Hardcover)

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.

11 of 12 people found the following review helpful:

5.0 out of 5 stars A very good introductory text book for intelligent systems, June 7, 2005

By 

Paras Jethwani (Melbourne) - See all my reviews
(REAL NAME)   

This review is from: Artificial Intelligence: A Guide to Intelligent Systems (Hardcover)

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.