On Extracting Arguments from Bayesian Network Representations of Evidential Reasoning

TY - CHAP

T1 - On Extracting Arguments from Bayesian Network Representations of Evidential Reasoning

AU - Keppens, Jeroen

PY - 2011/6

Y1 - 2011/6

N2 - 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.

AB - 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.

KW - evidential reasoning

KW - Bayesian networks

KW - Argumentation

U2 - 10.1145/2018358.2018380

DO - 10.1145/2018358.2018380

M3 - Chapter

SN - 978-1-4503-0755-0

SP - 141

EP - 150

BT - Proceedings of the 13th International Conference on Artificial Intelligence and Law

PB - ACM

ER -