A Modal Logic for Temporal and Jurisdictional Classifier Models
Artificial Intelligence
2025-10-16 v1
Abstract
Logic-based models can be used to build verification tools for machine learning classifiers employed in the legal field. ML classifiers predict the outcomes of new cases based on previous ones, thereby performing a form of case-based reasoning (CBR). In this paper, we introduce a modal logic of classifiers designed to formally capture legal CBR. We incorporate principles for resolving conflicts between precedents, by introducing into the logic the temporal dimension of cases and the hierarchy of courts within the legal system.
Cite
@article{arxiv.2510.13691,
title = {A Modal Logic for Temporal and Jurisdictional Classifier Models},
author = {Cecilia Di Florio and Huimin Dong and Antonino Rotolo},
journal= {arXiv preprint arXiv:2510.13691},
year = {2025}
}
Comments
18 pages, 2 figures. Extended version of a short paper accepted at PRIMA 2025. This is the authors' version of the work. It is posted here for your personal use