This paper presents an enhanced version of SDF-FuzzIA, a hybrid and modular system designed to support decision-making pro- cesses in geo-thematic domains. Built upon the Sustainability Decision Framework, the system integrates fuzzy ontologies, fuzzy rule-based sys- tems, and a large language model equipped with Retrieval-Augmented Generation capabilities. The proposed architecture aims to deliver accu- rate, explainable, and semantically grounded answers to complex queries involving geopolitical, economic, and environmental indicators in align- ment with the United Nations 2030 Agenda. A novel contribution of this work lies in the adoption of a Multi-Criteria Group Decision-Making methodology to support the construction of fuzzy ontologies, enabling the collaborative selection of membership functions and reducing sub- jectivity in knowledge modeling. Preliminary experiments show promis- ing results in replicating expert reasoning, while highlighting challenges related to scalability, consistency, and automation. This approach lays the groundwork for developing intelligent systems capable of transparent and context-aware decision support in data-rich and uncertainty-prone environments.

Castronovo, L., Filippone, G., Galici, M., La Rosa, G., Pavone, A.M., Tabacchi, M.E. (2026). SDF FuzzIA: A Fuzzy-Based, AI Support System for Decision-Making Frameworks. In M. Mario Pavone, C.A. Coello Coello, R. Cerulli, S. Greco, E.G. Talbi (a cura di), Decision Sciences Third Decision Science Alliance International Summer Conference, DSA ISC 2025, Catania, Italy, June 19–20, 2025, Proceedings (pp. 395-405) [10.1007/978-3-032-21811-7_28].

SDF FuzzIA: A Fuzzy-Based, AI Support System for Decision-Making Frameworks

Castronovo, Lydia;Filippone, Giuseppe;Galici, Mario;La Rosa, Gianmarco
;
Pavone, Arianna Maria;Tabacchi, Marco Elio
2026-01-01

Abstract

This paper presents an enhanced version of SDF-FuzzIA, a hybrid and modular system designed to support decision-making pro- cesses in geo-thematic domains. Built upon the Sustainability Decision Framework, the system integrates fuzzy ontologies, fuzzy rule-based sys- tems, and a large language model equipped with Retrieval-Augmented Generation capabilities. The proposed architecture aims to deliver accu- rate, explainable, and semantically grounded answers to complex queries involving geopolitical, economic, and environmental indicators in align- ment with the United Nations 2030 Agenda. A novel contribution of this work lies in the adoption of a Multi-Criteria Group Decision-Making methodology to support the construction of fuzzy ontologies, enabling the collaborative selection of membership functions and reducing sub- jectivity in knowledge modeling. Preliminary experiments show promis- ing results in replicating expert reasoning, while highlighting challenges related to scalability, consistency, and automation. This approach lays the groundwork for developing intelligent systems capable of transparent and context-aware decision support in data-rich and uncertainty-prone environments.
2026
Settore MATH-01/A - Logica matematica
Settore MATH-02/A - Algebra
Settore MATH-03/B - Probabilità e statistica matematica
Settore INFO-01/A - Informatica
9783032218100
9783032218117
Castronovo, L., Filippone, G., Galici, M., La Rosa, G., Pavone, A.M., Tabacchi, M.E. (2026). SDF FuzzIA: A Fuzzy-Based, AI Support System for Decision-Making Frameworks. In M. Mario Pavone, C.A. Coello Coello, R. Cerulli, S. Greco, E.G. Talbi (a cura di), Decision Sciences Third Decision Science Alliance International Summer Conference, DSA ISC 2025, Catania, Italy, June 19–20, 2025, Proceedings (pp. 395-405) [10.1007/978-3-032-21811-7_28].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/707471
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