Artificial Intelligence: A Guide to Intelligent Systems (2nd Edition) by Michael Negnevitsky

Artificial Intelligence: A Guide to Intelligent Systems (2nd Edition)

Features

Cover Type: Hard Cover with 440 pages

Published by: Addison Wesley

Edition: 2nd Edition November 12, 2004

Written in: English

ISBN 10 Number: 0321204662

ISBN 13 Number: 978-0321204660

Book Dimensions: 9.2 x 6.2 x 1.1 inches

Weighs: 1.7 pounds

Book Info
Provides a practical introduction to artificial intelligence that is less mathematically rigorous than other books on the market. Appropriate for programmers looking for an overview of all facets of artificial intelligence. --This text refers to an out of print or unavailable edition of this title.

Back Cover Copy

[Shelving Category] Artificial Intelligence/Soft Computing

Artificial Intelligence is often perceived as being a highly complicated, even frightening subject in Computer Science. This view is compounded by books in this area being crowded with complex matrix algebra and differential equations - until now. This book, evolving from lectures given to students with little knowledge of calculus, assumes no prior programming experience and demonstrates that most of the underlying ideas in intelligent systems are, in reality, simple and straightforward. Are you looking for a genuinely lucid, introductory text for a course in A.I or Intelligent Systems Design? Perhaps you¿re a non-computer science professional looking for a self-study guide to the state-of-the art in knowledge based systems? Either way, you can¿t afford to ignore this book.

Covers:

·        Rule-based expert systems

·        Fuzzy expert systems

·        Frame-based expert systems

·        Artificial neural networks

·        Evolutionary computation

·        Hybrid intelligent systems

·        Knowledge engineering

·        Data mining

New to this edition:

·        New demonstration rule-based system, MEDIA ADVISOR

·        New section on genetic algorithms

·        Four new case studies

·        Completely updated to incorporate the latest developments in this fast-paced field.

Dr Michael Negnevitsky is a Professor in Electrical Engineering and Computer Science at the University of Tasmania, Australia. The book has developed from lectures to undergraduates. Its material has also been extensively tested through short courses introduced at Otto-von-Guericke-Universit¿t Magdeburg, Institut Elektroantriebstechnik, Magdeburg, Germany, Hiroshima University, Japan and Boston University and Rochester Institute of Technology, USA

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 250 research publications including numerous journal articles, four patents for inventions and two books.

Reader 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. Comment | | (Report this)

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Updated on 6-4-2008.