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 175
The problem of finding a proof for ( Ex ) W ( x ) from S is an ordinary predicate
calculus theoremproving problem , but producing the satisfying instance for x
requires that the proof method be “ constructive . " We note that the prospect of ...
The problem of finding a proof for ( Ex ) W ( x ) from S is an ordinary predicate
calculus theoremproving problem , but producing the satisfying instance for x
requires that the proof method be “ constructive . " We note that the prospect of ...
Page 178
In our example , these steps produce the proof tree shown in Figure 5 . 7 with the
clause AT ( FIDO , SCHOOL ) at the root . This clause , then , is the appropriate
answer to the problem . We note that the answer statement has a form similar to ...
In our example , these steps produce the proof tree shown in Figure 5 . 7 with the
clause AT ( FIDO , SCHOOL ) at the root . This clause , then , is the appropriate
answer to the problem . We note that the answer statement has a form similar to ...
Page 185
The constant A could have been a variable without invalidating the proof shown
in Figure 5 . 12 . It can be shown ( Luckham and Nilsson ( 1971 ) ] that in the
answer - extracting process it is correct to replace any Skolem functions in the ...
The constant A could have been a variable without invalidating the proof shown
in Figure 5 . 12 . It can be shown ( Luckham and Nilsson ( 1971 ) ] that in the
answer - extracting process it is correct to replace any Skolem functions in the ...
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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 |