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 134
Formulas built by connecting other formulas by Vs are called disjunctions , and
each of the component formulas is called a disjunct . Any disjunction composed
of wffs is also a wff . The truth values of conjunctions and disjunctions are ...
Formulas built by connecting other formulas by Vs are called disjunctions , and
each of the component formulas is called a disjunct . Any disjunction composed
of wffs is also a wff . The truth values of conjunctions and disjunctions are ...
Page 205
If both proofs succeed , we have a proof based simply on the disjunction ( A V B )
, and it wouldn ' t matter which of A or B was true . In Figure 6 . 4 , the
descendants of the node labeled by ( A V B ) are connected to it by a 2 -
connector ; thus ...
If both proofs succeed , we have a proof based simply on the disjunction ( A V B )
, and it wouldn ' t matter which of A or B was true . In Figure 6 . 4 , the
descendants of the node labeled by ( A V B ) are connected to it by a 2 -
connector ; thus ...
Page 373
To represent a disjunction , we need some way of setting off those nodes and
arcs that are the disjuncts . In a linear ... For a disjunction , each disjunctive
predicate is drawn within the enclosure , and the enclosure is labeled DIS . Thus ,
the ...
To represent a disjunction , we need some way of setting off those nodes and
arcs that are the disjuncts . In a linear ... For a disjunction , each disjunctive
predicate is drawn within the enclosure , and the enclosure is labeled DIS . Thus ,
the ...
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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 |