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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CHAPTER 4 THE PREDICATE CALCULUS IN AI In many applications , the
information to be encoded into the global database of a production system
originates from descriptive statements that are difficult or unnatural to represent
by simple ...
The designer of a representation selects the alphabet of predicates and terms
that he will use and defines what the elements of this alphabet will mean . In the
predicate calculus , a wff can be given an interpretation by assigning a ...
CHAPTER 9 STRUCTURED OBJECT REPRESENTATIONS As we discussed in
chapter 4 , there are many ways to represent a body of knowledge in the
predicate calculus . The appropriateness of a representation depends on the
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PRODUCTION SYSTEMS AND AI
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