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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Any deleter of Cuj might ( as an F - rule ) destroy this precondition for F - rule j ;
thus the order in which deleters occur relative to F - rule j is important . If the
deleter is a descendant of rule j in the graph , we have special problems . ( We
are not ...
During the second phase of this problem , DCOMP might specify that F - rule 2
occur before F - rule 4 so that we can delete rule 5 . Further , F - rule 2 should
occur before F - rule 3 to avoid deleting the CLEAR ( C ) condition of F - rule 2 .
Now if ...
Because this derivation occurs so often with structured objects , it is usually built
into the matcher . ... Variables that occur in fact structures have implicit universal
quantification in all formulas in which they appear , and variables that occur in ...
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