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 Intelligenceevolved 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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... tip nodes that have not yet been selected for expansion . ( Some nodes may have no successors at all , so it is ... node ( except the root node ) of a tree 65 GRAPH - SEARCH STRATEGIES.
... tip nodes , he would choose that node having the largest evaluation . Therefore , the ( MAX node ) parent of MIN tip nodes is assigned a backed - up value equal to the maximum of the evaluations of the tip nodes . On the other hand , if ...
... tip nodes . If this tip node could be reached first in a depth - first search , the number of cutoffs would be maximal . When the number of cutoffs is maximal , a minimal number of tip nodes need to be generated and evaluated . Suppose ...
PRODUCTION Systems and AI
SEARCH Strategies FOR
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