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
We show a 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 ...
We show a 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
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 partial , candidate solution
graphs ...
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 partial , candidate solution
graphs ...
Page 237
Such a candidate solution graph is a final solution graph if its associated
substitution is consistent . In our example , matching the remaining nonterminal
leaf nodes of Figure 6 . 24 with facts fails to produce a consistent solution graph
because ...
Such a candidate solution graph is a final solution graph if its associated
substitution is consistent . In our example , matching the remaining nonterminal
leaf nodes of Figure 6 . 24 with facts fails to produce a consistent solution graph
because ...
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Contents
PROLOGUE | 1 |
PRODUCTION SYSTEMS AND AI | 17 |
SEARCH STRATEGIES FOR | 53 |
Copyright | |
10 other sections not shown
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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(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 global database 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 |