TY - JOUR
AU1 - Keppens, Jeroen
AB - Bayesian networks (BN) and argumentation diagrams (AD) are two predominant approaches to legal evidential reasoning, that are often treated as alternatives to one another. This paper argues that they are, instead, complimentary and proposes the beginnings of a method to employ them in such a manner. The Bayesian approach tends to be used as a means to analyse the findings of forensic scientists. As such, it constitutes a means to perform evidential reasoning. The design of Bayesian networks that accurately and comprehensively represent the relationships between investigative hypotheses and evidence remains difficult and sometimes contentious, however. Argumentation diagrams are representations of reasoning, and are used as a means to scrutinise reasoning (among other applications). In evidential reasoning, they tend to be used to represent and scrutinise the way humans reason about evidence. This paper examines how argumentation diagrams can be used to scrutinise Bayesian evidential reasoning by developing a method to extract argument diagrams from BN.
TI - Argument diagram extraction from evidential Bayesian networks
JF - Artificial Intelligence and Law
DO - 10.1007/s10506-012-9121-z
DA - 2012-03-20
UR - https://www.deepdyve.com/lp/springer-journals/argument-diagram-extraction-from-evidential-bayesian-networks-DbL87EZ1YD
SP - 109
EP - 143
VL - 20
IS - 2
DP - DeepDyve
ER -