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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We can always eliminate some of these interpretations by adding additional
formulas to the state description ; for ... Even though a finite conjunction of
formulas describes a family of states , we often loosely speak of the state
described by the ...
A B - rule that transforms a goal G into a subgoal G ' is logically based on the
corresponding F - rule that when applied to a state description matching G '
produces a state description matching G . We know that the application of an F -
rule to ...
First , an EL predicate is used to state that the object described by the unit is a
member of some set . ( If the object described by the unit had been a set itself ,
then an SS predicate would have been used to state that it was a subset of some
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