Causal models versus reason models in Bayesian networks for legal evidence

نویسندگان

چکیده

Abstract In this paper we compare causal models with reason in the construction of Bayesian networks for legal evidence. models, arrows network are drawn from causes to effects. a model, instead towards evidence, factum probandum probans . We explore differences between and observe several distinct advantages models. Reason better aligned philosophy inference, as they model reasons up-dating beliefs. suited measuring combined support prior probability guilt that reflects number possible perpetrators is accommodated more easily

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ژورنال

عنوان ژورنال: Synthese

سال: 2022

ISSN: ['0039-7857', '1573-0964']

DOI: https://doi.org/10.1007/s11229-022-03953-y