<p>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.</p>
<p>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.</p>
<p><b>The Knowledge You Need</b></p>
<p>This completely rewritten and updated edition of <i>Artificial Intelligence</i> reflects the revolutionary progress made since the previous edition was published.</p>
<p>Part I is about <b>representing knowledge</b> and about <b>reasoning methods</b> 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.</p>
<p>Part II is about <b>learning</b>, 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.</p>
<p>Part III is about <b>visual perception</b> and <b>language understanding</b>. 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.</p>
<p><b>Special Features of this Edition</b></p>
<ul>
<li>Based on extensive teaching experience</li>
<li>Semiformal representation and procedure specifications bring the ideas to within a step or two of implementation and highlight unifying themes.</li>
<li>Application examples provide a glimpse of the ideas at work in real-world systems.</li>
<li>Powerful ideas and principles are identified and emphasized.</li>
</ul>
<p>0201533774B04062001</p>
<p>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.
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