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
Results 1-3 of 35
Page 184
GOAL WFFS CONTAINING UNIVERSALLY QUANTIFIED VARIABLES A problem
arises when the goal wff contains universally quantified variables . These
universally quantified variables become existentially quantified in the negation of
the ...
GOAL WFFS CONTAINING UNIVERSALLY QUANTIFIED VARIABLES A problem
arises when the goal wff contains universally quantified variables . These
universally quantified variables become existentially quantified in the negation of
the ...
Page 205
For goal wffs containing existentially or universally quantified variables , we use a
Skolemization process that is dual to that used for facts and rules . Universal
variables in goals are replaced by Skolem functions of the existential variables in
...
For goal wffs containing existentially or universally quantified variables , we use a
Skolemization process that is dual to that used for facts and rules . Universal
variables in goals are replaced by Skolem functions of the existential variables in
...
Page 212
Applying this unifying composition to the goal literals used in the solution yields ~
TERRIER ( FIDO ) V NOISY ( FIDO ) , which is the instance of the goal wff that our
system has proved . This instantiated expression can thus be taken as the ...
Applying this unifying composition to the goal literals used in the solution yields ~
TERRIER ( FIDO ) V NOISY ( FIDO ) , which is the instance of the goal wff that our
system has proved . This instantiated expression can thus be taken as the ...
What people are saying - Write a review
We haven't found any reviews in the usual places.
Contents
PROLOGUE | 1 |
PRODUCTION SYSTEMS AND AI | 17 |
SEARCH STRATEGIES FOR | 53 |
Copyright | |
8 other sections not shown
Other editions - View all
Common terms and phrases
achieve actions algorithm AND/OR graph answer applied arcs Artificial Intelligence assertions 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 evaluation example expression F-rule fact Figure formula function given goal goal node 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 |