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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... prove this result using induction on the depth of a node in the A , search tree at termination . First , we prove that if A , expands a node n having zero depth in its search tree , then so will A ,. But , in this case , n = s . If s is ...
... prove that Sam , say , is an animal by first setting up the subgoal of proving that he is a cat and , failing in ... prove that Sam is not a cat , it is efficient to attempt to prove that he is not an animal . Again , search is ...
... prove the goal by rule - based means . One might also want to build one other important operation into the matcher , namely , an operation in which an inherited Skolem function node must be proved equal to a constant node . Consider the ...
Contents
PROLOGUE | 1 |
PRODUCTION SYSTEMS AND AI | 17 |
SEARCH STRATEGIES FOR | 53 |
Copyright | |
10 other sections not shown