Fuzzy Multi-Context Systems

Lei Yang, Yisong Wang, Hongp-Bo Hu, Ren-Yan Feng, J. Liu

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Multi-context systems provide an effective representation and reasoning framework for integrating heterogeneousknowledge obtained from different sources and have been appliedin different fields. Because many application fields in real life haveto deal with uncertain and fuzzy knowledge, the present workaims to combine the multi-context system and fuzzy logic theoryeffectively and systematically to deal with the representationand reasoning of uncertainty in heterogeneous contexts. Thecurrent research in this area is still relatively limited, especiallyin terms of systematic integration. Specifically, the present workproposes a class of heterogeneous non-monotonic fuzzy multicontext systems based on non-monotonic multi-context systems, in which an abstract logic is proposed to capture differenttypes of logic and is used as a theoretical basis for fuzzymulti-context knowledge representation and setting up bridgingrules to integrate heterogeneous knowledge. Fuzzy equilibria areused to describe the semantics of fuzzy multi-context systems.The syntactic and semantic framework of heterogeneous nonmonotonic fuzzy multi-context systems is then systematicallyestablished. Finally, we show that the proposed fuzzy multi-context system not only extends the non-monotonic multi-contextsystem to fuzzy settings, but also could expand the probabilisticmulti-context system and the possibility multi-context system inthe similar way.
Original languageEnglish
Pages (from-to)1-15
Number of pages15
JournalIEEE Transactions on Fuzzy Systems
Early online date8 Jul 2022
Publication statusE-pub ahead of print - 8 Jul 2022


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