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Artificial Intelligence (Anglais) Broché – 30 avril 1992


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Descriptions du produit

Quatrième de couverture

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.


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Biographie de l'auteur

About Patrick Henry Winston

Well-known author Patrick Henry Winston teaches computer science and directs the Artificial Intelligence Laboratory at theMassachusetts Institute of Technology.



0201533774AB04062001



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Amazon.com: 13 commentaires
25 internautes sur 28 ont trouvé ce commentaire utile 
Very useful and well written; an industry perspective: 17 août 1999
Par Un client - Publié sur Amazon.com
Format: Broché
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 internautes sur 13 ont trouvé ce commentaire utile 
A truly excellent survey of the field of AI 18 juin 1999
Par Un client - Publié sur Amazon.com
Format: Broché
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 internautes sur 20 ont trouvé ce commentaire utile 
Good as an undergraduate text 18 décembre 1998
Par Un client - Publié sur Amazon.com
Format: Broché
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).
6 internautes sur 7 ont trouvé ce commentaire utile 
Rich AI Illustrations 30 décembre 1998
Par Un client - Publié sur Amazon.com
Format: Broché
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.
34 internautes sur 50 ont trouvé ce commentaire utile 
Miserable AI book - avoid at all costs 20 décembre 2003
Par David Elder - Publié sur Amazon.com
Format: Broché
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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