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
... given by k ( n , t , ) . We let h * ( n ) be the minimum of all of the k ( n , t1 ) over the entire set of goal nodes { t ; } . Thus , h * ( n ) is the cost of the minimal cost path from n to a goal node , and any path from node n to a ...
... given by k ( n , t , ) . We let h * ( n ) be the minimum of all of the k ( n , t1 ) over the entire set of goal nodes { t ; } . Thus , h * ( n ) is the cost of the minimal cost path from n to a goal node , and any path from node n to a ...
Page 122
... given a backed - up value , this value is computed . Now consider the situation occurring at that stage of the depth - first search immediately after node A and all of its successors have been generated , but before node B is generated ...
... given a backed - up value , this value is computed . Now consider the situation occurring at that stage of the depth - first search immediately after node A and all of its successors have been generated , but before node B is generated ...
Page 313
... given action in a given state , that is , the preconditions of the action match that state description . PACT ( a , s ) states that it is possible to perform action a in state s . For our action trans , we thus have : 12 { HOLDS [ clear ...
... given action in a given state , that is , the preconditions of the action match that state description . PACT ( a , s ) states that it is possible to perform action a in state s . For our action trans , we thus have : 12 { HOLDS [ clear ...
Contents
PROLOGUE | 1 |
PRODUCTION SYSTEMS AND AI | 17 |
SEARCH STRATEGIES FOR | 53 |
Copyright | |
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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