On extracting arguments from Bayesian network representations of evidential reasoning

Abstract

Bayesian networks are a predominant approach to analyse the findings of forensic scientists. In part, this is due to the way the Bayesian approach fits the scientific method employed in forensic practice. The design of Bayesian networks that accurately and comprehensively represent the relationships between investigative hypotheses and evidence remains difficult and sometimes contentious, however. Recent research has shown that argumentation can inform the construction of Bayesian networks. But argumentation is a distinct approach to evidential reasoning with its on representation formalisms. This issue could be alleviated if it were easy to represent Bayesian networks as argumentation diagrams. This position paper presents an investigation into the similarities, differences and synergies between Bayesian networks and argumentation diagrams and shows a first version of an algorithm to extract argumentation diagrams from Bayesian networks.