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 41
A large AI system called DENDRAL can propose plausible structures for rather
complex compounds . ... The production system operates on this database to
increase its degree of structure : Initially , the database describes no chemical ...
A large AI system called DENDRAL can propose plausible structures for rather
complex compounds . ... The production system operates on this database to
increase its degree of structure : Initially , the database describes no chemical ...
Page 381
In order for a goal network structure to match a fact network structure , the formula
associated with the goal structure must unify with some sub - conjunction of the
formulas associated with the fact structure . In these examples , we merely have ...
In order for a goal network structure to match a fact network structure , the formula
associated with the goal structure must unify with some sub - conjunction of the
formulas associated with the fact structure . In these examples , we merely have ...
Page 406
CONSE structure ( appropriately instantiated ) can then be added to the fact
network . To use a network implication as a backward rule , the CONSE structure
( regarded as a fact ) must match the goal structure . Then , the ANTE structure ...
CONSE structure ( appropriately instantiated ) can then be added to the fact
network . To use a network implication as a backward rule , the CONSE structure
( regarded as a fact ) must match the goal structure . Then , the ANTE structure ...
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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 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 |