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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... rule is selected , and if it doesn't lead to a solution , the intervening ... applications and backups to illustrate how backtracking might be applied to ... rule selection is not arbitrary but is instead guided by information ...
... rule is applicable if the global database contains a symbol matching its ... applications . If we continue to apply ( irrevocably ) the reverse rules RI ... rule applications and the resulting global databases by an interest- ing ...
... rule applied to a derivation graph can be regarded as producing a new derivation graph . The rule application adds ... applications to that derivation graph and to its descendants along an optimal path to termination . When used to evaluate ...
Contents
PROLOGUE | 1 |
PRODUCTION SYSTEMS AND AI | 17 |
SEARCH STRATEGIES FOR | 53 |
Copyright | |
10 other sections not shown