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 240
If the system then generates some subgoal of P2 that contains the literal Pi , it can
use RGR between ~ P1 and Pl . An ... converting this goal to the subgoal P2
while adding Pl to the set of facts that can be used in proving P2 or its subgoals .
If the system then generates some subgoal of P2 that contains the literal Pi , it can
use RGR between ~ P1 and Pl . An ... converting this goal to the subgoal P2
while adding Pl to the set of facts that can be used in proving P2 or its subgoals .
Page 252
One of the subgoals produced by R4 is recognized as similar to the main goal .
Producing a subgoal having this sort of similarity suggests , to the control strategy
, the appropriateness of applying the induction rule , RI , to the main goal .
One of the subgoals produced by R4 is recognized as similar to the main goal .
Producing a subgoal having this sort of similarity suggests , to the control strategy
, the appropriateness of applying the induction rule , RI , to the main goal .
Page 291
The subgoal description is constructed as follows : ( 1 ) Regress the ( unmatched
) expression ON ( B , C ) through stack ( A , B ) yielding ON ( B ... Another
example illustrates how subgoals having existentially quantified variables are
created .
The subgoal description is constructed as follows : ( 1 ) Regress the ( unmatched
) expression ON ( B , C ) through stack ( A , B ) yielding ON ( B ... Another
example illustrates how subgoals having existentially quantified variables are
created .
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Common terms and phrases
achieve actions algorithm AND/OR graph answer applied arcs Artificial Intelligence 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 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 |