Saved in:
| Main Author: | |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2503.05702 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866916646797443072 |
|---|---|
| author | Fernandez-Peralta, Raquel |
| author_facet | Fernandez-Peralta, Raquel |
| contents | Fuzzy implication functions are a key area of study in fuzzy logic, extending the classical logical conditional to handle truth degrees in the interval $[0,1]$. While existing literature often focuses on a limited number of families, in the last ten years many new families have been introduced, each defined by specific construction methods and having different key properties. This survey aims to provide a comprehensive and structured overview of the diverse families of fuzzy implication functions, emphasizing their motivations, properties, and potential applications. By organizing the information schematically, this document serves as a valuable resource for both theoretical researchers seeking to avoid redundancy and practitioners looking to select appropriate operators for specific applications. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_05702 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Comprehensive Survey of Fuzzy Implication Functions Fernandez-Peralta, Raquel Artificial Intelligence Logic in Computer Science Fuzzy implication functions are a key area of study in fuzzy logic, extending the classical logical conditional to handle truth degrees in the interval $[0,1]$. While existing literature often focuses on a limited number of families, in the last ten years many new families have been introduced, each defined by specific construction methods and having different key properties. This survey aims to provide a comprehensive and structured overview of the diverse families of fuzzy implication functions, emphasizing their motivations, properties, and potential applications. By organizing the information schematically, this document serves as a valuable resource for both theoretical researchers seeking to avoid redundancy and practitioners looking to select appropriate operators for specific applications. |
| title | A Comprehensive Survey of Fuzzy Implication Functions |
| topic | Artificial Intelligence Logic in Computer Science |
| url | https://arxiv.org/abs/2503.05702 |