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An Argumentative Explanation Framework for Generalized Reason Model with Inconsistent Precedents

Published: October 22, 2025 | arXiv ID: 2510.19263v1

By: Wachara Fungwacharakorn, Gauvain Bourgne, Ken Satoh

Potential Business Impact:

Helps AI understand laws with messy rules.

Business Areas:
Predictive Analytics Artificial Intelligence, Data and Analytics, Software

Precedential constraint is one foundation of case-based reasoning in AI and Law. It generally assumes that the underlying set of precedents must be consistent. To relax this assumption, a generalized notion of the reason model has been introduced. While several argumentative explanation approaches exist for reasoning with precedents based on the traditional consistent reason model, there has been no corresponding argumentative explanation method developed for this generalized reasoning framework accommodating inconsistent precedents. To address this question, this paper examines an extension of the derivation state argumentation framework (DSA-framework) to explain the reasoning according to the generalized notion of the reason model.

Page Count
10 pages

Category
Computer Science:
Artificial Intelligence