Principles of Artificial IntelligenceA 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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... algorithm selects node 1 for expansion . ( We assume unit arc costs . ) When node 1 is expanded , its single successor , node 2 , is generated . But node 2 , with parent node 3 in the search tree , had previously been generated , and ...
... algorithm . The value of g ( n ) for certain nodes may decrease if the search tree is altered in step 7. ) Notice ... algorithm using this evaluation function for ordering nodes , algorithm A. Note that when h = 0 and g = d ( the depth ...
... algorithm expands fewer nodes than another does not imply that it is more efficient . The more informed algorithm may indeed have to make more costly computations , which would destroy efficiency . Nevertheless , the number of nodes ...
Contents
PROLOGUE | 1 |
PRODUCTION SYSTEMS AND AI | 17 |
SEARCH STRATEGIES FOR | 53 |
Copyright | |
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