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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One of the first successful Al systems for understanding limited fragments of
natural language is described in a book by Winograd ( 1972 ) . The book by
Newell et al . ( 1973 ) describes the five - year goals of a research project to
develop a ...
Setting up a backward - directed production system in the case of the 8 - puzzle is
simple because the goal is described by an explicit state . We can also set up
backward - directed production systems when the goal is described by a
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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PRODUCTION SYSTEMS AND AI
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