Principles of Artificial Intelligence
A 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 problems . For these reasons , theorem proving is an extremely important topic in the study of AI methods . 0.1.5 . ROBOTICS The problem of controlling the physical actions of a mobile robot might not seem to require ...
... theorem proving . Resolu- tion theorem proving is thoroughly explained in books by Chang and Lee ( 1973 ) , Loveland ( 1978 ) , and Robinson ( 1979 ) . Bledsoe and his co - workers have developed impressive theorem - prov- ing systems ...
... theorem - proving systems is for proving theorems in mathematics and logic . A less obvious , but important , use of them is in intelligent information retrieval systems where deductions must be performed on a database of facts in order ...
PRODUCTION Systems and AI
SEARCH Strategies FOR
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