A first-order logic for reasoning under uncertainty using rough sets |
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| Authors: | Simon Parsons Miroslav Kubat |
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| Affiliation: | (1) Advanced Computation Laboratory, Imperial Cancer Research Fund, PO Box 123, WC2A 3PX Lincoln's Inn Fields, London, UK;(2) Department of Medical Informatics, Institute of Biomedical Engineering, Graz University of Technology, Brockmangasse 41, A-8010 Graz, Austria |
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| Abstract: | Reasoning with uncertain information is a problem of key importance when dealing with knowledge from real situations. Obtaining the precise numbers required by many uncertainty-handling formalisms can be a problem when building real systems. The theory of rough sets allows us to handle uncertainty without the need for precise numbers, and so has some advantages in such situations. The authors develop a set of symbolic truth values based upon rough sets which may be used to augment predicate logic, and provide methods for combining these truth values so that they may be propagated when augmented logic formulae are used in automated reasoning. |
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| Keywords: | Uncertainty rough sets possible worlds rules of inference resolution principle theorem proving |
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