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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straightforward : It follows if there are literals among the facts that unify with each
of the precondition literals and if all of the mgu ' s are consistent ( that is , if these
mgu ' s have a unifying composition ) . If such a match can be found , we say that
Therefore , if a goal expression contains a literal , L , that unifies with one of the
literals in the add list of an F - rule , then we know that if we produce a state
description that matches appropriate instances of the preconditions of that F - rule
, the ...
F - rule 1 deletes a precondition of F - rule 2 , and vice versa . They cannot both
be first ! ( Sacerdoti ( 1977 ) called this type of conflict a " double cross . " ) The
blame for the unavoidable deletion conflict might be assigned to the substitutions
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