Principles of Artificial Intelligence
A classic introduction to artificial intelligence intended to bridge the gap between theory and practice, "Principles of Artificial Intelligence" describes fundamental AI ideas that underlie applications such as natural language processing, automatic programming, robotics, machine vision, automatic theorem proving, and intelligent data retrieval. Rather than focusing on the subject matter of the applications, the book is organized around general computational concepts involving the kinds of data structures used, the types of operations performed on the data structures, and the properties of the control strategies used.
"Principles of Artificial Intelligence"evolved from the author's courses and seminars at Stanford University and University of Massachusetts, Amherst, and is suitable for text use in a senior or graduate AI course, or for individual study.
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In a set - of - support refutation , each resolution has the flavor of a backward
reasoning step because it uses a clause originating from the goal wff , or one of
its descendants . Each of the resolvents in a set - of - support refutation might
Formalizing commonsense physics must be distinguished from the rather precise
mathematical models of the physics of solids , liquids and gases . The latter are
probably too cumbersome to support commonsense reasoning about physical ...
Collins ( 1978 ) stresses the importance of meta - knowledge in plausible
reasoning . ( We discuss the subject of meta - knowledge below . ) Zadeh ( 1979 )
invokes the ideas of fuzzy sets to deal with problems of approximate reasoning .
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