Abstract
The paper starts with ideas of possibility qualification and certainty qualification for specifying the possible range of a variable whose value is ill-known. The notion of possibility which is used for that purpose is not the standard one in possibility theory, although the two notions of possibility can be related. Based on these considerations four distinct types of rules with different semantics involving gradedness and uncertainty are then introduced. The combination operations which appear for taking advantage of the available knowledge are all derived from the intended semantics of the rules. The processing of these four types of rules is studied in detail. Fuzzy rules modelling preference in decision processes are also discussed.
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Dubois, D., Prade, H. (1992). Fuzzy rules in knowledge-based systems. In: Yager, R.R., Zadeh, L.A. (eds) An Introduction to Fuzzy Logic Applications in Intelligent Systems. The Springer International Series in Engineering and Computer Science, vol 165. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-3640-6_3
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DOI: https://doi.org/10.1007/978-1-4615-3640-6_3
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