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 135
A formula built by connecting two formulas with a → is called an implication . The
left - hand side of an implication is called the antecedent . and the right - hand
side is called the consequent . If both the antecedent and the consequent are wffs
...
A formula built by connecting two formulas with a → is called an implication . The
left - hand side of an implication is called the antecedent . and the right - hand
side is called the consequent . If both the antecedent and the consequent are wffs
...
Page 199
This restriction is a bit less severe than it appears because implications having
antecedents consisting of a disjunction of literals can be written as multiple rules ;
for example , the implication ( LI V L2 ) → W is equivalent to the pair of rules L1 W
...
This restriction is a bit less severe than it appears because implications having
antecedents consisting of a disjunction of literals can be written as multiple rules ;
for example , the implication ( LI V L2 ) → W is equivalent to the pair of rules L1 W
...
Page 404
The simplicity of the unit syntax makes representing implications that are much
more complex than those we have ... To use a network implication as a forward
rule , the ANTE structure ( regarded as a goal ) must match existing network fact ...
The simplicity of the unit syntax makes representing implications that are much
more complex than those we have ... To use a network implication as a forward
rule , the ANTE structure ( regarded as a goal ) must match existing network fact ...
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Contents
PROLOGUE | 1 |
PRODUCTION SYSTEMS AND AI | 17 |
SEARCH STRATEGIES FOR | 53 |
Copyright | |
8 other sections not shown
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Common terms and phrases
achieve actions algorithm AND/OR graph answer applied arcs Artificial Intelligence assertions 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 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 |