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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Many of these problems can be attacked by the methods discussed in this book .
A classical example is the traveling salesman ' s problem , where the problem is
to find a minimum distance tour , starting at one of several cities , visiting each ...
Several of these problems ( including the traveling salesman problem ) are
members of a class that computational theorists call NP - complete .
Computational theorists rank the difficulty of various problems on how the worst
case for the time ...
A solution to the problem is an appropriate sequence of moves , such as “ move
tile 6 down , move tile 8 down , . . . , etc . ” To solve a problem using a production
system , we must specify the global database , the rules , and the control strategy
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