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 77
Page 204
Goal Nodes Rules : A CAD B = EAG Fact ( A V B ) Fig . 6 . 4 An AND / OR graph
satisfying termination . simple goal expressions . ) Goal literals ( as well as rules )
can be used to add descendants to the AND / OR graph . When one of the goal ...
Goal Nodes Rules : A CAD B = EAG Fact ( A V B ) Fig . 6 . 4 An AND / OR graph
satisfying termination . simple goal expressions . ) Goal literals ( as well as rules )
can be used to add descendants to the AND / OR graph . When one of the goal ...
Page 213
GOAL EXPRESSIONS IN AND / OR FORM Our backward system is able to deal
with goal expressions of arbitrary form . We first convert the goal wff to AND / OR
form by the same sort of process used to convert a fact expression . We eliminate
...
GOAL EXPRESSIONS IN AND / OR FORM Our backward system is able to deal
with goal expressions of arbitrary form . We first convert the goal wff to AND / OR
form by the same sort of process used to convert a fact expression . We eliminate
...
Page 264
We first encounter GOAL ( BOSSOF ? u ? v ) . Since no facts match this goal , we
look for B - rules and find BR1 . The pattern match merely passes along the
existential variables . The computational environment is now as shown in Figure
6 .
We first encounter GOAL ( BOSSOF ? u ? v ) . Since no facts match this goal , we
look for B - rules and find BR1 . The pattern match merely passes along the
existential variables . The computational environment is now as shown in Figure
6 .
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 |