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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Nilsson ' s ( 1974 ) survey describes the field in the early 1970s and contains
many references . Michie ' s ( 1974 ) book contains several of his articles on Al .
Raphael ' s ( 1975 ) book and Winston ' s ( 1977 ) book are easy - to - read and ...
Now we consider the process of applying a rule of the form ( L W ) to an AND /
OR graph , where L is a literal , W is a wff in AND / OR form , and all expressions
might contain variables . The rule is applicable if the AND / OR graph contains a ...
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 ... produced by a backward application of
an F - rule must certainly contain instances of the preconditions of that F - rule .
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