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Artificial Intelligence (Addison-Wesley series in computer science) Hardcover – August 18, 1977

3.6 out of 5 stars 15 customer reviews

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--This text refers to the Paperback edition.

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Editorial Reviews

Amazon.com Review

This book is one of the oldest and most popular introductions to artificial intelligence. An accomplished artificial intelligence (AI) scientist, Winston heads MIT's Artificial Intelligence Laboratory, and his hands-on AI research experience lends authority to what he writes. Winston provides detailed pseudo-code for most of the algorithms discussed, so you will be able to implement and test the algorithms immediately. The book contains exercises to test your knowledge of the subject and helpful introductions and summaries to guide you through the material. --This text refers to the Paperback edition.

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 Need

This 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 --This text refers to the Paperback edition.
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Product Details

  • Series: Addison-Wesley series in computer science
  • Hardcover: 460 pages
  • Publisher: Addison-Wesley Educational Publishers Inc; 1 edition (August 18, 1977)
  • Language: English
  • ISBN-10: 0201084546
  • ISBN-13: 978-0201084542
  • Product Dimensions: 8.9 x 6.6 x 1 inches
  • Shipping Weight: 1.1 pounds
  • Average Customer Review: 3.6 out of 5 stars  See all reviews (15 customer reviews)
  • Amazon Best Sellers Rank: #1,476,538 in Books (See Top 100 in Books)

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Customer Reviews

Top Customer Reviews

Format: Paperback
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.
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By A Customer on December 18, 1998
Format: Paperback
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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Format: Paperback
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.
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Format: Paperback Verified Purchase
Some chapters covers great deal of information and it is pretty clear in this book. (R&N information overloads sometimes)
Pretty much worth four starts.

Example
==========================
Chapter 21 compared to R&N chapter 18 my opinion is it is better in this book on basic theory.
R&N information overloads in most cases it diverts busy reader (working students) getting the basics first.
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By A Customer on December 29, 1998
Format: Paperback
This is a good supplement to "AI - A Modern Approach by Russell and Norvig". The students and myself found the examples and illustration to be of great value in the understanding of the concepts. Would be great if authors could links references on the web for more information. Good book for the delivery of AI at foundation level.
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Format: Paperback
Winston's book is really terrible. I mean truly repellently, malignantly bad. "Can it really be as bad as all that?" you wonder. Yes!! It's that bad!! For starters, the book is poorly organized. Topics that logically belong together are often several chapters apart. There is no overall structure to the book. It seems like a collection of topics in AI that were hastily assembled without concern for thematic organization or flow. For example, the forward and backward chaining algorithms are presented in a chapter (Ch. 7) on rule-based systems, but are not even mentioned in the chapter (Ch. 13) on logic! Perceptron training is presented AFTER backpropagation! Contrast this with the much better book by Russell and Norvig, which uses the theme of intelligent agents as a continuing motivation throughout, and which groups related topics into logically arranged chapters.
The examples in Winston are atrocious. The main example in the backpropagation chapter is some kind of classification network with a bizarre topography. This example is so trivial and weird that it totally fails to illustrate the strengths of backpropagation. The explanations of generalization and overfitting in backprop training are awful.
The only chapter of this book that is not an unmitigated pedagogical disaster is the chapter on genetic algorithms, although better introductions exist (e.g. Melanie Mitchell).
A further annoyance is the placement of all the exercises at the end of the book instead of the end of the chapters to which they correspond.
Avoid this book. It is truly horrible, and vastly superior books on AI are readily available at comparable prices.
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Format: Paperback
My business used this book to help us rethink our analysis of credit and prepaid card fraud. While the material itself has been around for some time, it helped us develop new methods of detecting potential fraud.
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Format: Paperback Verified Purchase
This book is decent but it is showing its age both in terms of content and style. The theory explored is still relevant and it is a good companion to an AI course.
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