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 5
Several automatic theorem proving programs have been developed that possess
some of these same skills to a limited degree . The study of theorem proving has
been significant in the development of Al methods . The formalization of the ...
Several automatic theorem proving programs have been developed that possess
some of these same skills to a limited degree . The study of theorem proving has
been significant in the development of Al methods . The formalization of the ...
Page 13
THEOREM PROVING Early applications of Al ideas to proving theorems were
made by Gelernter ( 1959 ) to plane geometry ; and by Newell , Shaw , and
Simon ( 1957 ) to propositional logic . The resolution principle of Robinson ( 1965
) ...
THEOREM PROVING Early applications of Al ideas to proving theorems were
made by Gelernter ( 1959 ) to plane geometry ; and by Newell , Shaw , and
Simon ( 1957 ) to propositional logic . The resolution principle of Robinson ( 1965
) ...
Page 154
One obvious and direct use of theorem - proving systems is for proving theorems
in mathematics and logic . A less obvious , but important , use of them is in
intelligent information retrieval systems where deductions must be performed on
a ...
One obvious and direct use of theorem - proving systems is for proving theorems
in mathematics and logic . A less obvious , but important , use of them is in
intelligent information retrieval systems where deductions must be performed on
a ...
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Contents
PROLOGUE | 1 |
PRODUCTION SYSTEMS AND AL | 17 |
SEARCH STRATEGIES FOR | 53 |
Copyright | |
12 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 backward block called chapter clauses CLEAR(C complete component condition conjunction consider consistent contains control strategy corresponding cost database deduction Deleters described direction discussed evaluation example expression F-rule fact Figure formula function given global database goal goal wff HANDEMPTY heuristic implication important initial instance involves JOHN knowledge labeled language literals logically 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 resolvent 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 |