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 217
... consistent solution graph for this problem in Figure 6.10 . The fact nodes are shown double - boxed , and rule applications are labeled by the rule number . To verify the consistency of this solution graph , we compute the unifying ...
... consistent solution graph for this problem in Figure 6.10 . The fact nodes are shown double - boxed , and rule applications are labeled by the rule number . To verify the consistency of this solution graph , we compute the unifying ...
Page 218
Nils J. Nilsson. then checking it for consistency . If this candidate graph is not consistent , the search must continue until a consistent one is found . A more sophisticated strategy would involve checking for consistency as the ...
Nils J. Nilsson. then checking it for consistency . If this candidate graph is not consistent , the search must continue until a consistent one is found . A more sophisticated strategy would involve checking for consistency as the ...
Page 237
... consistent . In our example , matching the remaining nonterminal leaf nodes of Figure 6.24 with facts fails to produce a consistent solution graph because the solution of this problem requires more generality than can be obtained by ...
... consistent . In our example , matching the remaining nonterminal leaf nodes of Figure 6.24 with facts fails to produce a consistent solution graph because the solution of this problem requires more generality than can be obtained by ...
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 |