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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Page 99
... labeled by a compound database has a set of AND successor nodes , each labeling one of the component databases . In the other case , a parent node labeled by a component database has a set of OR successor nodes , each labeling the ...
... labeled by a compound database has a set of AND successor nodes , each labeling one of the component databases . In the other case , a parent node labeled by a component database has a set of OR successor nodes , each labeling the ...
Page 210
... labeling a literal node , n , of the graph , we can add a match arc ( labeled by the mgu ) directed from node n to a new descendant goal node labeled by L. The same goal literal can be used a number of times , creating multiple goal ...
... labeling a literal node , n , of the graph , we can add a match arc ( labeled by the mgu ) directed from node n to a new descendant goal node labeled by L. The same goal literal can be used a number of times , creating multiple goal ...
Page 215
... labeled by L ' that unifies with L. The result of applying the rule is to add a match arc from the node labeled by L ' to a new descendant node labeled by L. This new node is the root node of the AND / OR graph representation of Wu ...
... labeled by L ' that unifies with L. The result of applying the rule is to add a match arc from the node labeled by L ' to a new descendant node labeled by L. This new node is the root node of the AND / OR graph representation of Wu ...
Contents
PROLOGUE | 1 |
PRODUCTION SYSTEMS AND AI | 17 |
SEARCH STRATEGIES FOR | 53 |
Copyright | |
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Common terms and phrases
achieve actions algorithm AND/OR graph answer applied arcs Artificial Intelligence assume attempt backtracking backward block called chapter clause CLEAR CLEAR(C complete component condition consider consistent contains control strategy corresponding cost database deduction Deleters described direction discussed efficient evaluation example expression F-rule fact Figure formula function given goal goal stack goal wff HANDEMPTY heuristic important initial involves JOHN knowledge labeled language literals logic match methods move namely node Note obtained occur ONTABLE(A operation path possible precondition predicate calculus problem procedure production system proof prove quantified reasoning refutation represent representation resolution result robot rule satisfied selected sequence shown in Figure simple solution graph solve specify statement step STRIPS structure subgoal substitutions successors Suppose symbols termination theorem unifying unit University variables
Bibliographic information
| Title | Principles of Artificial Intelligence Symbolic computation |
| Author | Nils J. Nilsson |
| Edition | illustrated |
| Publisher | Tioga Publishing Company, 1980 |
| Original from | the University of Michigan |
| Digitized | 15 Nov 2007 |
| ISBN | 0935382011, 9780935382013 |
| Length | 476 pages |
| Export Citation | BiBTeX EndNote RefMan |