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 92
In Figure 2 . 13 we illustrate how penetrance varies with path length for various
values of B . To the extent that the effective branching factor is reasonably
independent of path length , it can be used to give a prediction of how many
nodes might ...
In Figure 2 . 13 we illustrate how penetrance varies with path length for various
values of B . To the extent that the effective branching factor is reasonably
independent of path length , it can be used to give a prediction of how many
nodes might ...
Page 110
An AND / OR search graph that results from applying the rewrite rules to an initial
global database consisting of the single symbol , T , is shown in Figure 3 . 4 .
There is an interesting manner in which the rewrite rules of our example can be ...
An AND / OR search graph that results from applying the rewrite rules to an initial
global database consisting of the single symbol , T , is shown in Figure 3 . 4 .
There is an interesting manner in which the rewrite rules of our example can be ...
Page 381
The match is successful in Figure 9 . 10 , but it is unsuccessful in Figure 9 . 11 . In
any representational scheme there are often several alternative representations
for basically the same information . Since our definition of structure matching ...
The match is successful in Figure 9 . 10 , but it is unsuccessful in Figure 9 . 11 . In
any representational scheme there are often several alternative representations
for basically the same information . Since our definition of structure matching ...
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Contents
PRODUCTION SYSTEMS AND AI | 17 |
SEARCH STRATEGIES FOR | 53 |
SEARCH STRATEGIES FOR DECOMPOSABLE | 99 |
Copyright | |
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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 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 search tree selected sequence shown in Figure simple solution graph solve specify statement step STRIPS structure subgoal substitutions successors Suppose symbols termination theorem tree 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 |