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 161
... Resolution - based systems are designed to produce proofs by contradiction or refutations . In a resolution refutation , we first negate the goal wff and then add the negation to the set , S. This expanded set is then converted to a set ...
... Resolution - based systems are designed to produce proofs by contradiction or refutations . In a resolution refutation , we first negate the goal wff and then add the negation to the set , S. This expanded set is then converted to a set ...
Page 163
... RESOLUTION REFUTATIONS We can think of a system for producing resolution refutations as a production system . The global database is a set of clauses , and the rule schema is resolution . Instances of this schema are applied to pairs of ...
... RESOLUTION REFUTATIONS We can think of a system for producing resolution refutations as a production system . The global database is a set of clauses , and the rule schema is resolution . Instances of this schema are applied to pairs of ...
Page 172
... resolutions are performed is crucial to the efficiency of resolution systems . Since we do not concentrate on applications of resolution refutation systems in this book , the interested reader is referred to the citations at the end of ...
... resolutions are performed is crucial to the efficiency of resolution systems . Since we do not concentrate on applications of resolution refutation systems in this book , the interested reader is referred to the citations at the end of ...
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 Artificial Intelligence assume attempt backtracking backward block called chapter clause CLEAR CLEAR(C complete component condition consider consistent contains control strategy corresponding cost database deduction Deleters described direction discussed efficient 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 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 |