In this section
@inproceedings{Alfano:2025:ijcai.2025/481,
author = {Alfano, G and Gould, A and Leofante, F and Rago, A and Toni, F},
doi = {ijcai.2025/481},
pages = {4321--4329},
publisher = {IJCAI},
title = {Counterfactual explanations under model multiplicity and their use in computational argumentation},
url = {http://dx.doi.org/10.24963/ijcai.2025/481},
year = {2025}
}
TY - CPAPER
AB - Counterfactual explanations (CXs) are widely recognised as an essential technique for providing recourse recommendations for AI models. However, 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. In this paper, we propose novel qualitative and quantitative definitions of CXs based on explicit, nested quantification over (groups) of model decisions. We also study properties of these notions and identify decision problems of interest therefor. While 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. We then illustrate the suitability of our CXs for model multiplicity in legal and healthcare contexts, before analysing the complexity of the associated decision problems.
AU - Alfano,G
AU - Gould,A
AU - Leofante,F
AU - Rago,A
AU - Toni,F
DO - ijcai.2025/481
EP - 4329
PB - IJCAI
PY - 2025///
SP - 4321
TI - Counterfactual explanations under model multiplicity and their use in computational argumentation
UR - http://dx.doi.org/10.24963/ijcai.2025/481
ER -
