Oosterhuis, T.S. (2016) Integration of argumentative, narrative and probabilistic reasoning in court. Bachelor's Thesis, Artificial Intelligence.
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Abstract
In order to trace and potentially prevent miscarriages of justice old court cases are analyzed. However there is no standardized method to model these cases yet. In this paper two methods are evaluated, both with a new approach to integrate scenario-based and probability-based ways of reasoning with evidence. One method uses Bayesian network idioms to model scenarios and evidence, and the other uses standard probability theory and propositional logic to represent scenarios for and against which arguments (in the form of evidence) can be made. The advantages of both methods are evaluated by means of a comparative case study of a solved Dutch murder case. The main advantage of the Bayesian method being its scenario-structure and the main advantage of the logico-probabilistic method being its formal approach which, unlike the Bayesian approach, doesn’t require more numbers than are available. The logico-probabilistic method is then extended with the scenario-structure of the Bayesian method, creating a third method which uses propositional logic idioms to create scenarios every event of which is treated as a hypothesis for and against which arguments can be made. The model which results from testing the extended method on the case study is as specific as the Bayesian model which doesn’t require elicitation of unknown numbers.
| Item Type: | Thesis (Bachelor's Thesis) |
|---|---|
| Supervisor name: | Verheij, B. |
| Degree programme: | Artificial Intelligence |
| Thesis type: | Bachelor's Thesis |
| Language: | English |
| Date Deposited: | 15 Feb 2018 08:11 |
| Last Modified: | 02 May 2019 10:52 |
| URI: | https://fse.studenttheses.ub.rug.nl/id/eprint/13721 |
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