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. |
From inside the book
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... assume that were MAX to choose among tip nodes , he would choose that node having the largest evaluation . Therefore ... assuming that MAX would choose that node with the largest backed - up value while MIN would choose that node with ...
... assuming that A is true and then attempt to prove the goal assuming B is true . If both proofs succeed , we have a proof based ... assume that any existential variables in facts and rules have been Skolemized . For goal wffs containing ...
... assume that the control strategy guides the generation of the AND / OR graph by pursuing a depth - first search for a consistent solution graph . In selecting a literal node within a partial solution graph to match against a B - rule ...
Contents
PROLOGUE | 1 |
PRODUCTION SYSTEMS AND AI | 17 |
SEARCH STRATEGIES FOR | 53 |
Copyright | |
10 other sections not shown