Inferring New Classifications in Legal Case-Based Reasoning

被引:0
|
作者
Di Florio, Cecilia [2 ]
Liu, Xinghan [1 ]
Lorini, Emiliano [1 ]
Rotolo, Antonino [2 ]
Sartor, Giovanni [2 ]
机构
[1] Univ Toulouse, IRIT CNRS, Toulouse, France
[2] Univ Bologna, Alma Human AI, Bologna, Italy
来源
关键词
Case-based reasoning; Modal Logic for classifiers; Explainable AI; Defeasible reasoning; EXPLANATION; MODEL;
D O I
10.3233/FAIA230942
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This article continues the research initiated in [1,2], which established a connection between Boolean classifiers and legal case-based reasoning. We relax the assumption that case bases are such that all situations have been decided in favour of the defendant or the plaintiff and we introduce an inductive strategy for assigning plausible outcomes to undecided cases. Using counterfactual reasoning, we propose a method to determine whether, at each step of the induction, a feature is a factor, i.e., it consistently favours a single outcome, or is irrelevant, i.e., it is does not favour any outcome, or is ambiguous, i.e., it favours opposite outcomes.
引用
收藏
页码:23 / 32
页数:10
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