• 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