- Hardcover: 750 pages
- Publisher: Addison Wesley; 3 edition (30 April 1992)
- Language English
- ISBN-10: 0201533774
- ISBN-13: 978-0201533774
- Product Dimensions: 24.2 x 19.7 x 3.5 cm
- Average Customer Review: 4.0 out of 5 stars See all reviews (2 customer reviews)
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Amazon Bestsellers Rank:
957,186 in Books (See Top 100 in Books)
- #48 in Books > Computers & Internet > Computer Science > Information Systems > Expert Systems
- See Complete Table of Contents
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Product Description
Product Description
This is the all-time bestselling introduction to artificial intelligence. The third edition retains the best features of the earlier works, including superior readability, currency, and excellence in the selection of examples. Winston emphasizes how artificial intelligence can be viewed from an engineering or a scientific point of view. The new edition offers comprehensive coverage of more material, and many of the ideas presented are enhanced with a variety of side pieces, including application examples such as the Westinghouse nuclear fuel plant optimizer.
From the Back Cover
This book explains how it is possible for computers to reason and perceive, thus introducing the field called artificial intelligence. From the book, you learn why the field is important, both as a branch of engineering and as a science.
If you are a computer scientist or an engineer, you will enjoy the book, because it provides a cornucopia of new ideas for representing knowledge, using knowledge, and building practical systems. If you are a psychologist, biologist, linguist, or philosopher, you will enjoy the book because it provides an exciting computational perspective on the mystery of intelligence.
The Knowledge You NeedThis completely rewritten and updated edition of Artificial Intelligence reflects the revolutionary progress made since the previous edition was published.
Part I is about representing knowledge and about reasoning methods that make use of knowledge. The material covered includes the semantic-net family of representations, describe and match, generate and test, means-ends analysis, problem reduction, basic search, optimal search, adversarial search, rule chaining, the rete algorithm, frame inheritance, topological sorting, constraint propagation, logic, truth maintenance, planning, and cognitive modeling.
Part II is about learning, the sine qua non of intelligence. Some methods involve much reasoning; others just extract regularity from data. The material covered includes near-miss analysis, explanation-based learning, knowledge repair, case recording, version-space convergence, identification-tree construction, neural-net training, perceptron convergence, approximation-net construction, and simulated evolution.
Part III is about visual perception and language understanding. You learn not only about perception and language, but also about ideas that have been a major source of inspiration for people working in other subfields of artificial intelligence. The material covered includes object identification, stereo vision, shape from shading, a glimpse of modern linguistic theory, and transition-tree methods for building practical natural-language interfaces.
Special Features of this Edition- Based on extensive teaching experience
- Semiformal representation and procedure specifications bring the ideas to within a step or two of implementation and highlight unifying themes.
- Application examples provide a glimpse of the ideas at work in real-world systems.
- Powerful ideas and principles are identified and emphasized.
0201533774B04062001
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Customer Reviews
Most Helpful Customer Reviews
1 of 1 people found the following review helpful
Format:Hardcover
I bought this book to prepare myself for an introductory AI class. The book gave me a good overview on the different aspects of Artificial Intelligence, but it didn't go into any depth at all.
First of all I think this book lacked a good historical and philosophical introduction.
Then, if you are not a computer science student, you might enjoy reading the chapters about search etc, but for a CS major this is stuff you alrady know better than what is written in this book!
The book also misses a good overview on logic and how logic is used for automated reasoning in AI. There are a few applications for which they use logic but I found them (because of lack of a good AR) rather confusing at first.
The rest of the book gives a good high level overview on different aspects of learning, vision, natural language processing, ... but don't expect anything thourough.
I woul recommend this book to a interested reader in need for a good overview and willing to learn some applications and algorithms. For a CS major I would recommend: "Artificial Intelligence: A Modern Approach" which is much more technical and covers a lot more.
3 of 5 people found the following review helpful
Format:Hardcover
Where is the 4th edition. This book is brilliant, it is clear, full of examples and covers all the key principles of AI in one book. For practical support LisP (by Winston and Horn) is excellent for putting the theory into practice.
Most Helpful Customer Reviews on Amazon.com (beta)
Amazon.com:
11 reviews
23 of 26 people found the following review helpful
Very useful and well written; an industry perspective:
17 Aug 1999
Format:Hardcover
Suppose you are, like me, a software engineer who never actually studied CS beyond junior level undergraduate 'data structures'... and now you have to work on something involving complicated pattern matching... this is how to do it: buy this book and Sipser's on the Theory of Computation. After digesting them (which is easy if you're as good with logical mathematics as the typical software engineer), you should be able to read current literature in either field, and will have a deep, fundamental understanding of how to best solve whatever problem you're working on. That's what worked for me, anyway. An excellent book, as is Sipser's.
12 of 13 people found the following review helpful
A truly excellent survey of the field of AI
18 Jun 1999
Format:Hardcover
Having purchased this book as a supplement to Winston's course at MIT, I can very highly recommend it as a very comprehensive, up-to-date, well written text summarizing the field. The book covers essentially all of the topics pertenant in modern AI with enough detail for a complete implementation without being overly technical. I strongly recommend it to anybody looking to build intelligent systems or to anybody simply perusing the field for abstract ideas.
17 of 20 people found the following review helpful
Good as an undergraduate text
18 Dec 1998
Format:Hardcover
This book serves as an excellent introduction to what is in reality a very broad topic. Not meant for serious research into any one particular area of AI, the text is excellent for undergraduates(with questions that aren't worded too badly - a rarity in AI texts). More advanced AI topics are given short shrift(as is typical), but are covered in sufficient depth to give students an idea of how they work(three chapters worth if I'm not mistaken, more than most texts).
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