Abstract
Legal cases involve reasoning with evidence and with the development of a software support tool in mind, a formal foundation for evidential reasoning is required. Three approaches to evidential reasoning have been prominent in the literature: argumentation, narrative and probabilistic reasoning. In this paper a combination of the latter two is proposed.
In recent research on Bayesian networks applied to legal cases, a number of legal idioms have been developed as recurring structures in legal Bayesian networks. A Bayesian network quantifies how various variables in a case interact. In the narrative approach, scenarios provide a context for the evidence in a case. A method that integrates the quantitative, numerical techniques of Bayesian networks with the qualitative, holistic approach of scenarios is lacking.
In this paper, a method is proposed for modeling several scenarios in a single Bayesian network. The method is tested by doing a case study. Two new idioms are introduced: the scenario idiom and the merged scenarios idiom. The resulting network is meant to assist a judge or jury, helping to maintain a good overview of the interactions between relevant variables in a case and preventing tunnel vision by comparing various scenarios.
In recent research on Bayesian networks applied to legal cases, a number of legal idioms have been developed as recurring structures in legal Bayesian networks. A Bayesian network quantifies how various variables in a case interact. In the narrative approach, scenarios provide a context for the evidence in a case. A method that integrates the quantitative, numerical techniques of Bayesian networks with the qualitative, holistic approach of scenarios is lacking.
In this paper, a method is proposed for modeling several scenarios in a single Bayesian network. The method is tested by doing a case study. Two new idioms are introduced: the scenario idiom and the merged scenarios idiom. The resulting network is meant to assist a judge or jury, helping to maintain a good overview of the interactions between relevant variables in a case and preventing tunnel vision by comparing various scenarios.
Original language | English |
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Title of host publication | Proceedings of the 14th International Conference on Artificial Intelligence and Law (ICAIL 2013) |
Place of Publication | New York (New York) |
Publisher | ACM Press |
Pages | 150-159 |
Number of pages | 10 |
Publication status | Published - 2013 |
Event | 14th International Conference on Artificial Intelligence and Law (ICAIL 2013) - Rome, Italy Duration: 10-Jun-2013 → 14-Jun-2013 |
Conference
Conference | 14th International Conference on Artificial Intelligence and Law (ICAIL 2013) |
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Country/Territory | Italy |
City | Rome |
Period | 10/06/2013 → 14/06/2013 |
Keywords
- Bayesian Networks
- Narrative
- Reasoning with evidence