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 Intelligence"evolved 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 310
Unfortunately , in Green ' s formulation , we must have assertions for each
relation not affected by an action . For example , we need the following assertion
to express that the blocks that are not moved stay in the same position : ( ON ( u ,
v , s ) ...
Unfortunately , in Green ' s formulation , we must have assertions for each
relation not affected by an action . For example , we need the following assertion
to express that the blocks that are not moved stay in the same position : ( ON ( u ,
v , s ) ...
Page 311
The problem can now be solved by finding a constructive proof of the goal
formula from the assertions . Any reasonable theorem - proving method might be
used . As already mentioned , Green used a resolution system in which the goal
was ...
The problem can now be solved by finding a constructive proof of the goal
formula from the assertions . Any reasonable theorem - proving method might be
used . As already mentioned , Green used a resolution system in which the goal
was ...
Page 314
In our example , the single frame assertion is : 14 { HOLDS ( v , s ) A DIFF [ v ,
clear ( 2 ) ] A DIFF [ v , on ( x , y ) ] } → HOLDS [ v , do ( trans ... Assertions 1 - 14 ,
then , express the basic knowledge needed by a problem solver for this example
.
In our example , the single frame assertion is : 14 { HOLDS ( v , s ) A DIFF [ v ,
clear ( 2 ) ] A DIFF [ v , on ( x , y ) ] } → HOLDS [ v , do ( trans ... Assertions 1 - 14 ,
then , express the basic knowledge needed by a problem solver for this example
.
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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 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 efficient evaluation example expanded expression F-rule fact Figure formula function given global database goal goal node goal stack goal wff HANDEMPTY heuristic important initial involves JOHN knowledge labeled language literals 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 unifying unit universal variables
Bibliographic information
| Title | Principles of Artificial Intelligence Symbolic computation |
| Author | Nils J. Nilsson |
| Edition | illustrated, reprint |
| Publisher | Morgan Kaufmann Publishers, 1986 |
| Original from | the University of Virginia |
| Digitized | 27 Jul 2009 |
| ISBN | 0934613109, 9780934613101 |
| Length | 476 pages |
| Subjects | › Reference / General |
| Export Citation | BiBTeX EndNote RefMan |