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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... theorem proving programs have been developed that possess some of these same skills to a limited degree . The study of theorem proving has been significant in the development of AI methods . The formalization of the deductive process ...
Nils J. Nilsson. 0.3.4 . THEOREM PROVING Early applications of AI ideas to proving theorems were made by Gelernter ( 1959 ) to plane geometry ; and by Newell , Shaw , and Simon ( 1957 ) to propositional logic . The resolution principle ...
... theorem - proving formula- tions have considerable theoretical interest and preceded STRIPS historically . We describe two alternative approaches for posing robot problems as theorem - proving problems . 7.6.1 . GREEN'S FORMULATION One ...
Contents
PROLOGUE | 1 |
PRODUCTION SYSTEMS AND AI | 17 |
SEARCH STRATEGIES FOR | 53 |
Copyright | |
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