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 240
... subgoal P2 while adding Pl to the set of facts that can be used in proving P2 or its subgoals . Then , if the system generates Pl as a subgoal of P2 , this subgoal can be matched against the assumed fact P1 . The process of converting ...
... subgoal P2 while adding Pl to the set of facts that can be used in proving P2 or its subgoals . Then , if the system generates Pl as a subgoal of P2 , this subgoal can be matched against the assumed fact P1 . The process of converting ...
Page 288
... subgoal expressions . One strategy is to use B - rules that are based on the F - rules that we have just discussed . A B - rule that transforms a goal G into a subgoal G ' is logically based on the corresponding F - rule that when ...
... subgoal expressions . One strategy is to use B - rules that are based on the F - rules that we have just discussed . A B - rule that transforms a goal G into a subgoal G ' is logically based on the corresponding F - rule that when ...
Page 292
... subgoals greatly reduces the subgoal space . In Figure 7.5 we show the results of applying some B - rules to our example goal . ( The tail of each B - rule arc is adjacent to that goal literal used to match a literal in the add list of ...
... subgoals greatly reduces the subgoal space . In Figure 7.5 we show the results of applying some B - rules to our example goal . ( The tail of each B - rule arc is adjacent to that goal literal used to match a literal in the add list of ...
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