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 219
If rule R5 is the only possible match for subgoal Q ( x ) , this inconsistency would
allow us to prune the subgoal U ( z ) from the graph . Solving U ( z ) cannot
contribute to a consistent solution graph . Notice , however , that subgoal S ( x )
can be ...
If rule R5 is the only possible match for subgoal Q ( x ) , this inconsistency would
allow us to prune the subgoal U ( z ) from the graph . Solving U ( z ) cannot
contribute to a consistent solution graph . Notice , however , that subgoal S ( x )
can be ...
Page 245
It turns out that the order ( F1 , F2 , R1 , R2 ) for rule and fact matching and the
order in which we have written the ... Beginning with the goal REVERSED ( cons
( 1 , cons ( 2 , NIL ) ) , y ) , we first check ( in the order F1 , F2 , RI , R2 ) for a match
.
It turns out that the order ( F1 , F2 , R1 , R2 ) for rule and fact matching and the
order in which we have written the ... Beginning with the goal REVERSED ( cons
( 1 , cons ( 2 , NIL ) ) , y ) , we first check ( in the order F1 , F2 , RI , R2 ) for a match
.
Page 278
If such a match can be found , we say that the precondition of the F - rule matches
the facts . We call the unifying composition , the match substitution . For a given F
- rule and state description , there may be many match substitutions .
If such a match can be found , we say that the precondition of the F - rule matches
the facts . We call the unifying composition , the match substitution . For a given F
- rule and state description , there may be many match substitutions .
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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 evaluation example 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 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 |