Modelling and Explaining Legal Case-Based Reasoners Through Classifiers - Archive ouverte HAL
Communication Dans Un Congrès Année : 2022

Modelling and Explaining Legal Case-Based Reasoners Through Classifiers

Résumé

This paper brings together factor-based models of case-based reasoning (CBR) and the logical specification of classifiers. Horty [8] has developed the factor-based models of precedent into a theory of precedential constraint. In this paper we combine binary-input classifier logic (BCL) to classifiers and their explanations given by Liu & Lorini [13, 14] with Horty’s account of factor-based CBR, since both a classifier and CBR map sets of features to decisions or classifications. We reformulate case bases in the language of BCL, and give several representation results. Furthermore, we show how notions of CBR can be analyzed by notions of classifier explanation.
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hal-04308074 , version 1 (26-11-2023)

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Xinghan Liu, Emiliano Lorini, Antonino Rotolo, Giovanni Sartor. Modelling and Explaining Legal Case-Based Reasoners Through Classifiers. 35th Annual Conference on Legal Knowledge and Information Systems (JURIX 2022), Dec 2022, Saarbrucken, Germany. pp.83-92, ⟨10.3233/faia220451⟩. ⟨hal-04308074⟩
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