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 167
... reasoning steps to occur in a simple fashion in the same production system . ( Forward reasoning steps correspond to resolutions between clauses that do not descend from the theorem to be proved . ) In Figure 5.3 we show a refutation ...
... reasoning steps to occur in a simple fashion in the same production system . ( Forward reasoning steps correspond to resolutions between clauses that do not descend from the theorem to be proved . ) In Figure 5.3 we show a refutation ...
Page 392
... reasoning might be somewhat more " convoluted " than those used in formal biology - an individual may be an element of more than one set , for example . Usually , though , useful hierarchies narrow toward a small number of sets at the ...
... reasoning might be somewhat more " convoluted " than those used in formal biology - an individual may be an element of more than one set , for example . Usually , though , useful hierarchies narrow toward a small number of sets at the ...
Page 424
... reasoning . ( We discuss the subject of meta - knowledge below . ) Zadeh ( 1979 ) invokes the ideas of fuzzy sets to deal with problems of approx- imate reasoning . The work on default reasoning and non - monotonic logic , cited at the ...
... reasoning . ( We discuss the subject of meta - knowledge below . ) Zadeh ( 1979 ) invokes the ideas of fuzzy sets to deal with problems of approx- imate reasoning . The work on default reasoning and non - monotonic logic , cited at the ...
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 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