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 Intelligence evolved 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 60
Note that no cell in row 6 is satisfactory ; each attempt to place a queen in that
row would fail . In such a circumstance , BACKTRACK would attempt to relocate
the queen in row 5 , moving it eventually to column 8. But a more detailed
analysis ...
Note that no cell in row 6 is satisfactory ; each attempt to place a queen in that
row would fail . In such a circumstance , BACKTRACK would attempt to relocate
the queen in row 5 , moving it eventually to column 8. But a more detailed
analysis ...
Page 291
Suppose we attempt to apply the B - rule version of unstack to the goal
expression ( CLEAR ( A ) A HANDEMPTY ) . The mgu is { A / y } . The regression
of HANDEMPTY through unstack ( x , A ) is F. Since no conjunction containing F
can be ...
Suppose we attempt to apply the B - rule version of unstack to the goal
expression ( CLEAR ( A ) A HANDEMPTY ) . The mgu is { A / y } . The regression
of HANDEMPTY through unstack ( x , A ) is F. Since no conjunction containing F
can be ...
Page 397
Our attempt to find a match must look back through al arcs incident on N1 , a2
arcs incident on N2 , etc. ( We assume that our implementation of the network
makes it easy to trace through arcs in the " reverse ” direction . ) Some of these
arcs ...
Our attempt to find a match must look back through al arcs incident on N1 , a2
arcs incident on N2 , etc. ( We assume that our implementation of the network
makes it easy to trace through arcs in the " reverse ” direction . ) Some of these
arcs ...
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Contents
PROLOGUE | 1 |
PRODUCTION SYSTEMS AND AI | 17 |
SEARCH STRATEGIES FOR | 53 |
Copyright | |
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Common terms and phrases
achieve actions algorithm AND/OR graph answer applied arcs assertions assume attempt backtracking backward block called chapter clause CLEAR(C complete component condition consider consistent contains control strategy corresponding cost database Deleters described direction discussed efficient evaluation example expanded 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 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 unifying unit universal variables
Bibliographic information
| Title | Principles of Artificial Intelligence |
| Author | Nils J. Nilsson |
| Edition | illustrated, reprint |
| Publisher | Morgan Kaufmann Publishers, 1986 |
| Original from | the University of Virginia |
| Digitized | 27 Jul 2009 |
| ISBN | 0934613109, 9780934613101 |
| Length | 476 pages |
| Subjects | › Reference / General |
| Export Citation | BiBTeX EndNote RefMan |