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 278
Each leads to a different instance of F - rule that can be applied . ... is applied to
the literals in the delete list ; and the ground instances thus obtained are deleted
from the old state description as the first step of constructing the new one .
Each leads to a different instance of F - rule that can be applied . ... is applied to
the literals in the delete list ; and the ground instances thus obtained are deleted
from the old state description as the first step of constructing the new one .
Page 288
Therefore , if a goal expression contains a literal , L , that unifies with one of the
literals in the add list of an F - rule , then we know that if we produce a state
description that matches appropriate instances of the preconditions of that F - rule
, the ...
Therefore , if a goal expression contains a literal , L , that unifies with one of the
literals in the add list of an F - rule , then we know that if we produce a state
description that matches appropriate instances of the preconditions of that F - rule
, the ...
Page 289
Let RIQ ; Fu ] be the regression of a literal Q through a ground instance Fu of an F
- rule with precondition , P , delete list , D , and add list , A . Then , if Qu is a literal
in Au , R [ Q ; Fu ) = T ( True ) else , if Qu is a literal in Du , R [ Q ; Fu ] = F ( False )
...
Let RIQ ; Fu ] be the regression of a literal Q through a ground instance Fu of an F
- rule with precondition , P , delete list , D , and add list , A . Then , if Qu is a literal
in Au , R [ Q ; Fu ) = T ( True ) else , if Qu is a literal in Du , R [ Q ; Fu ] = F ( False )
...
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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 |