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:
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Brief Research Report
Conceptual Analysis
Data Report
Editorial
FAIR² Data
General Commentary
Hypothesis and Theory
Methods
Mini Review
Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.
Article types
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
