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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Several automatic theorem proving programs have been developed that possess
some of these same skills to a limited degree . The study of theorem proving has
been significant in the development of Al methods . The formalization of the ...
THEOREM PROVING Early applications of Al ideas to proving theorems were
made by Gelernter ( 1959 ) to plane geometry ; and by Newell , Shaw , and
Simon ( 1957 ) to propositional logic . The resolution principle of Robinson ( 1965
One obvious and direct use of theorem - proving systems is for proving theorems
in mathematics and logic . A less obvious , but important , use of them is in
intelligent information retrieval systems where deductions must be performed on
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