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 275
... problems of interest in AI , however , the most natural formulations involve noncommutative systems . Typical problems of this sort are ones where goals are achieved by a sequence ( or program ) of actions . Robot problem solving and ...
... problems of interest in AI , however , the most natural formulations involve noncommutative systems . Typical problems of this sort are ones where goals are achieved by a sequence ( or program ) of actions . Robot problem solving and ...
Page 316
... problem - solving system is described in Fikes and Nilsson ( 1971 ) . The version of STRIPS discussed in this ... solving more difficult problems . Triangle tables play a key role in this process . The GPS system was developed by Newell ...
... problem - solving system is described in Fikes and Nilsson ( 1971 ) . The version of STRIPS discussed in this ... solving more difficult problems . Triangle tables play a key role in this process . The GPS system was developed by Newell ...
Page 447
... Problem - solving models and search strategies for pattern recognition . IEEE Trans . of Pattern Analysis and Machine Intelligence , PAM1-1 ( 2 ) , 193-201 . Klahr , P. 1978. Planning techniques for rule selection in deductive question ...
... Problem - solving models and search strategies for pattern recognition . IEEE Trans . of Pattern Analysis and Machine Intelligence , PAM1-1 ( 2 ) , 193-201 . Klahr , P. 1978. Planning techniques for rule selection in deductive question ...
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