{"type":"ScholarlyArticle","title":"Counterfactual Explanations Under Model Multiplicity and Their Use in Computational Argumentation","authors":[{"name":"Gianvincenzo Alfano","slug":"gianvincenzo-alfano","given":"Gianvincenzo","family":"Alfano","affiliation":""},{"name":"Adam Gould","slug":"adam-gould","given":"Adam","family":"Gould","affiliation":""},{"name":"Francesco Leofante","slug":"francesco-leofante","given":"Francesco","family":"Leofante","affiliation":""},{"name":"Antonio Rago","slug":"antonio-rago","given":"Antonio","family":"Rago","affiliation":""},{"name":"Francesca Toni","slug":"francesca-toni","given":"Francesca","family":"Toni","affiliation":""}],"abstract":"Counterfactual explanations (CXs) are widely recognised as an essential technique for providing recourse recommendations for AI models. \r\nHowever, it is not obvious how to determine CXs in model multiplicity scenarios, where equally performing but different models can be obtained for the same task. \r\nIn this paper, we propose novel qualitative and quantitative definitions of CXs based on explicit, nested quantification over (groups) of model decisions. \r\nWe also study properties of these notions and identify decision problems of interest therefor. \r\nWhile our CXs are broadly applicable, in this paper we instantiate them within computational argumentation where model multiplicity naturally emerges, e.g. with incomplete and case-based argumentation frameworks. \r\nWe then illustrate the suitability of our CXs for model multiplicity in legal and healthcare contexts, before analysing the complexity of the associated decision problems.","doi":"10.24963/ijcai.2025/481","url":"https://ijcai.org/proceedings/2025/481","pdf":"https://ijcai.org/proceedings/2025/0481.pdf","markdown":"https://ijcai.org/proceedings/2025/481.md","bibtex":"https://ijcai.org/proceedings/2025/bibtex/481","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":481,"pages":{"first":4321,"last":4329},"keywords":["Knowledge Representation and Reasoning: KRR: Argumentation","AI Ethics, Trust, Fairness: ETF: Explainability and interpretability"],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}