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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Therefore , the ( MAX node ) parent of MIN tip nodes is assigned a backed - up
value equal to the maximum of the ... After the parents of all tip nodes have been
assigned backed - up values , we back up values another level , assuming that ...
immediately that MIN will choose A . We can then assign A ' s parent the backed -
up value of – oo and proceed with the search , having saved the search effort of
generating and evaluating nodes B , C , and D . ( Note that the savings in search
backed - up values , the bounds on backed - up values can be revised . But we
note that : ( a ) The alpha values of MAX nodes ( including the start node ) can
never decrease , and ( b ) the beta values of MIN nodes can never increase .
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PRODUCTION SYSTEMS AND AI
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