Plausible reasoning in judicial proof: a computational argumentation perspective

Abstract

Abstract This study proposes a computational argumentation model for plausible reasoning in judicial proof, using the ASPIC+ framework to formalize and evaluate the plausibility of legal argumentation. The work distinguishes between plausibility and probability, suggesting that plausibility is more well suited to the inherently subjective nature of legal reasoning, because legal reasoning relies on external standards such as the credibility of sources and the reliability of evidence. The work emphasizes the dynamic nature of plausibility and presents a system that captures how plausibility evolves in response to challenges and counterarguments. The model introduces three levels of plausibility—apparent, validated, and stable—offering a structured approach to evaluate the strength of plausible arguments in judicial contexts. A detailed case study illustrates the practical applications of this approach, underscoring its potential to evaluate the judicial proof.