
Proceedings Paper
A Cause Based Method Of Knowledge Representation And Its Application To Lift SchedulingFormat | Member Price | Non-Member Price |
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Paper Abstract
The traditional way of encoding knowledge for an expert system is to use the Horn clause. This allows easy implementation of goal-oriented search procedures, but requires that the data base must be complete and consistent. An alternative scheme is to use cause based systems, where an identified cause can lead to one or more effects. With a knowledge base encoded in this way, it is possible to use a learning procedure to determine which effects are related to which cause. In this way rules can be continually inferred from the input data stream. The method has been sucessfully tried on two systems with dynamic properties. These are a lift scheduler and a system for discovering patterns of digits which are randomly embedded in noise.
Paper Details
Date Published: 26 March 1986
PDF: 6 pages
Proc. SPIE 0635, Applications of Artificial Intelligence III, (26 March 1986); doi: 10.1117/12.964158
Published in SPIE Proceedings Vol. 0635:
Applications of Artificial Intelligence III
John F. Gilmore, Editor(s)
PDF: 6 pages
Proc. SPIE 0635, Applications of Artificial Intelligence III, (26 March 1986); doi: 10.1117/12.964158
Show Author Affiliations
Alan Howson, Polytechnic of the South Bank (England)
Duncan Gillies, Imperial College of Science and Technology (England)
Published in SPIE Proceedings Vol. 0635:
Applications of Artificial Intelligence III
John F. Gilmore, Editor(s)
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