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 204
... literal node , n , of the graph , we add a new descendant of node n , labeled by the matching goal literal , to the graph . This descendant is called a goal node . Goal nodes ... nodes . ( At termination , the system has essentially inferred ...
... literal node , n , of the graph , we add a new descendant of node n , labeled by the matching goal literal , to the graph . This descendant is called a goal node . Goal nodes ... nodes . ( At termination , the system has essentially inferred ...
Page 206
... literal , W is a wff in AND / OR form , and all expressions might contain ... nodes and that include the newly added match arc . The clauses corresponding ... nodes of the solution graphs . These clauses are just those that could be ...
... literal , W is a wff in AND / OR form , and all expressions might contain ... nodes and that include the newly added match arc . The clauses corresponding ... nodes of the solution graphs . These clauses are just those that could be ...
Page 210
... literal nodes labeled by R ( A ) and Q ( x ) . If the same rule is applied more than once , it is important that ... literal , L , unifies with a literal L ' labeling a literal node , n , of the graph , we can add a match arc ( labeled ...
... literal nodes labeled by R ( A ) and Q ( x ) . If the same rule is applied more than once , it is important that ... literal , L , unifies with a literal L ' labeling a literal node , n , of the graph , we can add a match arc ( labeled ...
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 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 evaluation example expression F-rule fact Figure formula function given global database 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