Nowadays, fuzzy logic has become a formal and useful tool for computer science to deal with uncertain information and fuzzy information. It is worth noticing that t-norm based fuzzy logic is one of the important parts of fuzzy logic, including Esteva and Godo’s MTL, Hajek’s BL and MV. In the past, various algebraic structures have been proposed as the semantical systems of t-norm based fuzzy logics, for example, residuated lattices (include MTL-algebras, BL-algebras, R0-algebras, MV-algebras, FI-lattices), aggregation functions (include overlap functions, quasi-overlap functions) and their fuzzy implications.

Recently, artificial intelligence, big data, and decision-making have become hot spots of computer science and technology; data intelligence is the integration of the two, which requires a variety of fuzzy logic approaches to provide basic theory.

This Special Issue aims to promote close communication and cooperation in the research fields of fuzzy logic, various t-norm based fuzzy logic and their related algebraic systems, as well as applications in data intelligence. We welcome original research and review articles.

Potential topics include but are not limited to the following:

• T-norm based fuzzy logic with logical connectives
• Residuated lattices, MTL-algebras, BL-algebras and MV-algebras
• Overlap functions and their fuzzy implications
• Grouping functions and their fuzzy implications
• Fuzzy implication algebras