Re-consider : The integration of online dispute resolution and decision support systems
- Authors: Muecke, Nial , Stranieri, Andrew , Miller, Charlynn
- Date: 2008
- Type: Text , Conference paper
- Relation: Paper presented at 5th International Workshop on Online Dispute Resolution, in conjunction with the 21st International Conference on Legal Knowledge and Information Systems (JURIX 2008), Firenze, Italy : 13th December 2008
- Full Text:
- Description: Current approaches for the design of Online Dispute Resolution (ODR) systems involve the replication of Alternative Dispute Resolution practices such as mediation and negotiation. Though such systems have been found to be popular, there are concerns that these systems fail to take into account judicial practices. In this paper a system that supports disputants' decisions making when engaged in an online dispute is advanced. The system, Re-Consider, is an Australia Family Law ODR system, that is based on judicial reasoning modelled with Bayesian belief networks and provides disputants with decision support in the dispute. It is believed that this approach provides disputants with an online resolution process that will help them to reach outcomes that take judicial practices into account and presents a step toward more deliberative form of online dispute resolution.
- Description: 2003006782
Predictions with uncertainty to support fair outcomes in online legal disputes
- Authors: Muecke, Nial
- Date: 2006
- Type: Text , Conference paper
- Relation: Paper presented at CIMCA 2006, International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and International Commerce, Sydney : 29th November, 2006
- Full Text: false
- Reviewed:
- Description: 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.
- Description: E1
- Description: 2003001823
The role of emotional intelligence on the resolution of disputes involving the electronic health record
- Authors: Bellucci, Emilia , Venkatraman, Sitalakshmi , Muecke, Nial , Stranieri, Andrew
- Date: 2012
- Type: Text , Conference paper
- Relation: Fifth Australasian workshop on health informatics and knowledge management p. 3-12
- Full Text: false
- Reviewed:
An argument structure abstraction for Bayesian belief networks: Just outcomes in on-line dispute resolution
- Authors: Muecke, Nial , Stranieri, Andrew
- Date: 2008
- Type: Text , Conference proceedings
- Full Text:
- Description: There are many different approaches for settling disputes on-line, such as simple email systems, fixed bid systems and intelligent systems. However, to date there have been no attempts to integrate decision support methods into the dispute resolution process for the purpose of supporting outcomes that are consistent with judicial reasoning. This paper describes how a model of judicial reasoning can be used to assist divorcees with the resolution of property issues online, in a manner that is consistent with decisions a judge would make if the matter was heard in Court. The approach uses an argument based model of the discretionary nature of decisions made by judges in Australian Family Law. This is integrated with a protocol for online dispute dialogue. Predictions of the likelihood of alternates outcomes is achieved with a series of Bayesian Belief Networks
Automatic sleep stage identification: difficulties and possible solutions
- Authors: Sukhorukova, Nadezda , Stranieri, Andrew , Ofoghi, Bahadorreza , Vamplew, Peter , Saleem, Muhammad Saad , Ma, Liping , Ugon, Adrien , Ugon, Julien , Muecke, Nial , Amiel, Hélène , Philippe, Carole , Bani-Mustafa, Ahmed , Huda, Shamsul , Bertoli, Marcello , Levy, P , Ganascia, J.G
- Date: 2010
- Type: Text , Conference proceedings
- Full Text:
- Description: The diagnosis of many sleep disorders is a labour intensive task that involves the specialised interpretation of numerous signals including brain wave, breath and heart rate captured in overnight polysomnogram sessions. The automation of diagnoses is challenging for data mining algorithms because the data sets are extremely large and noisy, the signals are complex and specialist's analyses vary. This work reports on the adaptation of approaches from four fields; neural networks, mathematical optimisation, financial forecasting and frequency domain analysis to the problem of automatically determing a patient's stage of sleep. Results, though preliminary, are promising and indicate that combined approaches may prove more fruitful than the reliance on a approach.