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 63
We see that the problem of finding a sequence of rules transforming one database into another is equivalent to the problem of finding a path in a graph . Often it is convenient to assign positive costs to arcs , to represent the cost of ...
We see that the problem of finding a sequence of rules transforming one database into another is equivalent to the problem of finding a path in a graph . Often it is convenient to assign positive costs to arcs , to represent the cost of ...
Page 394
In Figure 9.20 we show , by dashed arcs , some of the possible a arcs that the matcher is permitted to seek . If it can find such an arc , the match is successful . Unless all of the goal arcs can be matched , the matcher terminates ...
In Figure 9.20 we show , by dashed arcs , some of the possible a arcs that the matcher is permitted to seek . If it can find such an arc , the match is successful . Unless all of the goal arcs can be matched , the matcher terminates ...
Page 397
Then , we look in the taxonomic hierarchy above each such node Ni to see if Ni inherits an ai arc to some Skolem ... say , x , is tied to constant fact nodes , N1 , N2 , . . . , Nk , by arcs labeled al , a2 , . . . , ak , respectively .
Then , we look in the taxonomic hierarchy above each such node Ni to see if Ni inherits an ai arc to some Skolem ... say , x , is tied to constant fact nodes , N1 , N2 , . . . , Nk , by arcs labeled al , a2 , . . . , ak , respectively .
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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 Artificial Intelligence assume attempt backtracking backward block called chapter clause CLEAR 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 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 |