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 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.

Artificial_intelligence_b07

Winston, Patrick Henry

Reading, Mass.: Addison-Wesley Pub. Co.

Da Capo Press, Incorporated

Hachette Books

Basic Books

Pearson

3rd ed., repr. with corrections 1993, Reading, Mass, 1993

3rd ed., Reading, Mass, Wokingham, United Kingdom, 1992

3rd ed., Reading, Mass, Massachusetts, 1992

United States, United States of America

3rd Edition, PS, 1992

1994

Includes bibliographical references (p. 693-724) and index.

Reprint of 3rd ed., 1992. Previous ed., 1984.
Includes bibliographical references (p. 693-724) and index.

xxv, 737 pages : 25 cm
Explains how it is possible for computers to reason and perceive, thus introducing the field called Artificial Intelligence. This book helps in learning why the field is important, both as a branch of engineering and as a science. It is aimed at computer scientists, engineers, psychologists, biologists, linguists and philosophers
Includes bibliographical references (pages 693-724) and index

2023-06-28