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 75
( The function k is undefined for nodes having no path between them . ) The cost
of a minimal cost path from node n to some particular goal node , ti , is then given
by k ( n , t ; ) . We let h * ( n ) be the minimum of all of the k ( n , ti ) over the entire ...
( The function k is undefined for nodes having no path between them . ) The cost
of a minimal cost path from node n to some particular goal node , ti , is then given
by k ( n , t ; ) . We let h * ( n ) be the minimum of all of the k ( n , ti ) over the entire ...
Page 122
Node A is now given the backed - up value of - 1 . At this point we know that the
backed - up value of the start node is bounded from below by – 1 . Depending on
the backed - up values of the other successors of the start node , the final backed
...
Node A is now given the backed - up value of - 1 . At this point we know that the
backed - up value of the start node is bounded from below by – 1 . Depending on
the backed - up values of the other successors of the start node , the final backed
...
Page 313
11 is then given by the following set of expressions : 1 POSS ( SO ) 2 HOLDS [ on
( A , D ) , SO ] 3 HOLDS ( on ( B , E ) , SO ] 4 HOLDS ( on ( C , F ) , SO ] 5 HOLDS (
clear ( A ) , SO ) 6 HOLDS [ clear ( B ) , SO ) 7 HOLDS ( clear ( C ) , So ] 8 ...
11 is then given by the following set of expressions : 1 POSS ( SO ) 2 HOLDS [ on
( A , D ) , SO ] 3 HOLDS ( on ( B , E ) , SO ] 4 HOLDS ( on ( C , F ) , SO ] 5 HOLDS (
clear ( A ) , SO ) 6 HOLDS [ clear ( B ) , SO ) 7 HOLDS ( clear ( C ) , So ] 8 ...
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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(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 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