Research Repository

A hybrid rule – neural approach for the automation of legal reasoning in the discretionary domain of family law in Australia

Stranieri, Andrew, Zeleznikow, John, Gawler, Mark and Lewis, Bryn (1999) A hybrid rule – neural approach for the automation of legal reasoning in the discretionary domain of family law in Australia. Artificial Intelligence and Law , 7 (2-3). pp. 153-183. ISSN 0924-8463

[img] Text
Restricted to Repository staff only

Download (181kB)


Few automated legal reasoning systems have been developed in domains of law in which a judicial decision maker has extensive discretion in the exercise of his or her powers. Discretionary domains challenge existing artificial intelligence paradigms because models of judicial reasoning are difficult, if not impossible to specify. We argue that judicial discretion adds to the characterisation of law as open textured in a way which has not been addressed by artificial intelligence and law researchers in depth. We demonstrate that systems for reasoning with this form of open texture can be built by integrating rule sets with neural networks trained with data collected from standard past cases. The obstacles to this approach include difficulties in generating explanations once conclusions have been inferred, difficulties associated with the collection of sufficient data from past cases and difficulties associated with integrating two vastly different paradigms. A knowledge representation scheme based on the structure of arguments proposed by Toulmin has been used to overcome these obstacles. The system, known as Split Up, predicts judicial decisions in property proceedings within family law in Australia. Predictions from the system have been compared to those from a group of lawyers with favourable results.

Item Type: Article
Uncontrolled Keywords: split Up, decision support system, neural networks, artificial intelligence, legal reasoning, family law
Subjects: Faculty/School/Research Centre/Department > School of Management and Information Systems
FOR Classification > 0806 Information Systems
Faculty/School/Research Centre/Department > School of Law
FOR Classification > 1801 Law
Depositing User: VUIR
Date Deposited: 22 Nov 2010 04:30
Last Modified: 23 May 2013 16:46
ePrint Statistics: View download statistics for this item

Repository staff only

View Item View Item

Search Google Scholar