DocumentCode :
3100926
Title :
Predictions with Uncertainty to Support Fair Outcomes in Online Legal Disputes
Author :
Muecke, Nial
Author_Institution :
Sch. of Inf. & Math. Sci., Univ. of Ballarat, Ballarat, VIC
fYear :
2006
fDate :
Nov. 28 2006-Dec. 1 2006
Firstpage :
218
Lastpage :
218
Abstract :
Alternative dispute resolutions systems are not uncommon in Australian family law, however to date these systems are largely negotiation based and are not designed for producing judicially fair outcomes. This paper proposes an online dispute resolution approach that aims to support divorcees to resolve property issues in a manner that is consistent with orders a judge would make if the matter was heard in court. The approach integrates a protocol for online dispute dialogue with an argument based model of judicial reasoning to structure the dispute. The likelihood of alternates outcomes is predicted with a series of Bayesian belief networks.
Keywords :
Bayes methods; law; Australian family law; Bayesian belief networks; argument based model; judicial reasoning; online dispute dialogue; online dispute resolution approach; online legal disputes; Australia; Bayesian methods; Computational intelligence; Intelligent systems; Knowledge based systems; Law; Legal factors; Predictive models; Protocols; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence for Modelling, Control and Automation, 2006 and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, International Conference on
Conference_Location :
Sydney, NSW
Print_ISBN :
0-7695-2731-0
Type :
conf
DOI :
10.1109/CIMCA.2006.164
Filename :
4052833
Link To Document :
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