{"type":"ScholarlyArticle","title":"Human-Readable Neuro-Fuzzy Networks from Frequent Yet Discernible Patterns in Reward-Based Environments","authors":[{"name":"John Wesley Hostetter","slug":"john-wesley-hostetter","given":"John Wesley","family":"Hostetter","affiliation":""},{"name":"Adittya Soukarjya Saha","slug":"adittya-soukarjya-saha","given":"Adittya Soukarjya","family":"Saha","affiliation":""},{"name":"Md Mirajul Islam","slug":"md-mirajul-islam","given":"Md Mirajul","family":"Islam","affiliation":""},{"name":"Tiffany Barnes","slug":"tiffany-barnes","given":"Tiffany","family":"Barnes","affiliation":""},{"name":"Min Chi","slug":"min-chi","given":"Min","family":"Chi","affiliation":""}],"abstract":"We propose self-organizing and simplifying neuro-fuzzy networks (NFNs) to yield transparent human-readable policies by exploiting fuzzy information granulation and graph theory. Deriving from social network analysis, we retain only the frequent-yet-discernible (FYD) patterns in NFNs and apply them to reward-based scenarios. The effectiveness of NFNs from FYD patterns is shown in classic control and a real-world classroom using an intelligent tutoring system to teach students.","doi":"10.24963/ijcai.2025/505","url":"https://ijcai.org/proceedings/2025/505","pdf":"https://ijcai.org/proceedings/2025/0505.pdf","markdown":"https://ijcai.org/proceedings/2025/505.md","bibtex":"https://ijcai.org/proceedings/2025/bibtex/505","volume":{"slug":"2025","title":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2025","url":"https://ijcai.org/proceedings/2025/","year":2025,"location":"Montreal, Canada","dates":"16-22 August 2025","editors":"James Kwok","isbn":"978-1-956792-06-5","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2025"},"section":"Knowledge Representation and Reasoning","track":"Main Track","number":505,"pages":{"first":4535,"last":4543},"keywords":["Humans and AI: HAI: Computer-aided education","Data Mining: DM: Frequent pattern mining","Knowledge Representation and Reasoning: KRR: Learning and reasoning","Machine Learning: ML: Neuro-symbolic methods/Abductive Learning"],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}