Modelling competing legal arguments using Bayesian networks

We have previously always tried to capture all of the competing hypotheses and evidence in a legal case in a single coherent Bayesian network model. But our new paper explains why this may not always be sensible and how to deal with it by using "competing" models. The full published version can be read here.

This work arose out of the highly successful Isaac Newton Institute Cambridge Programme on Probability and Statistics in Forensic Science.

Full reference:

Neil, M., Fenton, N. E., Lagnado, D. A. & Gill, R. (2019), "Modelling competing legal arguments using Bayesian Model Comparison and Averaging". Artificial Intelligence and Law https://doi.org/10.1007/s10506-019-09250-3 .The full published version can be read here

See also

• The Simonshaven murder case modelled as a Bayesian network
• Bayesian networks and argumentation 
• Challenging claims that probability theory is incompatible with legal reasoning
• Probability and statistics in forensics