The field of fuzzy system theory, which is grounded in fuzzy sets, provides robust solutions to complex problems involving fuzziness. Fuzzy systems excel at capturing the fuzzy features of human brain thinking and have an advantage in describing high-level knowledge from a macroscopic perspective. They are able to imitate human comprehensive inference to handle fuzzy information processing problems that are difficult to solve by conventional mathematical methods. Intelligent reasoning is an important core of fuzzy systems. The relevant application fields of intelligent reasoning in fuzzy systems involve automatic control, machine learning, pattern recognition, decision analysis, timing signal processing, human-computer dialogue systems, economic information systems, medical diagnosis systems, earthquake prediction systems, etc.

Fuzzy systems have strong interpretability, controllability, and credibility, which can also be well integrated at a deep level with deep learning, large models, etc. The connotation of intelligent reasoning in fuzzy systems includes logical algebra and reasoning, production fuzzy reasoning, granular computing and reasoning, and intelligent reasoning of large models, and so forth. Typical intelligent reasoning methods include the CRI (Compositional Rule of Inference) algorithm, the triple I algorithm, the QIP (Quintuple Implication Principle) algorithm, the BKS (Bandler-Kohout Subproduct) algorithm, the universal triple I algorithm, the UQI (Universal Quintuple Implicational) algorithm, and so on. Overall, intelligent reasoning in fuzzy systems is playing an increasingly important role in fields such as fuzzy classification, clustering, control, and machine learning.

This article collection aims to investigate the latest developments and future directions in intelligent reasoning for fuzzy systems. It seeks to delve into the underlying mechanisms, exploring their theoretical foundations and core methodologies while identifying practical application models. To gather further insights in the scope of intelligent reasoning in fuzzy systems, we welcome articles addressing, but not limited to:

- Intelligent reasoning
- Fuzzy logic
- Fuzzy reasoning
- Fuzzy control
- Fuzzy clustering
- Fuzzy classification
- Collaborative computing
- Machine learning
- Affective computing
- Granular computing

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Intelligent Reasoning in Fuzzy Systems: Latest Progress and Future Trends