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   Book Info

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Artificial Intelligence  
Author: Patrick Henry Winston
ISBN: 0201533774
Format: Handover
Publish Date: June, 2005
 
     
     
   Book 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.


Book Info
New edition explains how it is possible for computers to reason and perceive, thus introducing the field called artificial intelligence. Learn why the field is important, both as a branch of engineering and as a science. DLC: Artificial intelligence.


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


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

0201533774AB04062001




Artificial Intelligence

ANNOTATION

This is an eagerly awaited revision of the single bestselling introduction to Artificial Intelligence ever published. It retains the best features of the earlier works including superior readability, currency, and excellence in the selection of the examples.

FROM THE PUBLISHER

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 visualperception 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.

ACCREDITATION

About Patrick Henry Winston

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



     



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