Bisimulation and bisimilarity for fuzzy description logics under the G\"odel semantics
Linh Anh Nguyen, Quang-Thuy Ha, Ngoc Thanh Nguyen, Thi Hong Khanh, Nguyen, Thanh-Luong Tran

TL;DR
This paper introduces and analyzes fuzzy bisimulation and bisimilarity concepts for fuzzy description logics under G"odel semantics, extending classical notions to handle vagueness and imprecision in knowledge representation.
Contribution
It defines fuzzy and crisp bisimulation relations for fuzzy DLs with G"odel semantics, proving key invariance and Hennessy-Milner properties, and explores their applications in concept learning and interpretation minimization.
Findings
Fuzzy bisimulation invariance of concepts established.
Conditional invariance of TBoxes/ABoxes demonstrated.
Fuzzy bisimulation used to differentiate expressive power of fuzzy DLs.
Abstract
Description logics (DLs) are a suitable formalism for representing knowledge about domains in which objects are described not only by attributes but also by binary relations between objects. Fuzzy extensions of DLs can be used for such domains when data and knowledge about them are vague and imprecise. One of the possible ways to specify classes of objects in such domains is to use concepts in fuzzy DLs. As DLs are variants of modal logics, indiscernibility in DLs is characterized by bisimilarity. The bisimilarity relation of an interpretation is the largest auto-bisimulation of that interpretation. In DLs and their fuzzy extensions, such equivalence relations can be used for concept learning. In this paper, we define and study fuzzy bisimulation and bisimilarity for fuzzy DLs under the G\"odel semantics, as well as crisp bisimulation and strong bisimilarity for such logics extended…
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