Formalising Argumentative Story-based Analysis of Evidence

Floris Bex, Henry Prakken & Bart Verheij

In the present paper, we provide a formalised version of a merged argumentative and story-based approach towards the analysis of evidence. As an application, we are able to show how our approach sheds new light on inference to the best explanation with case evidence. More specifically, it will be clarified how the events in a case story that are considered to be proven abductively explain the otherwise unproven events of the case story. We compare our approach with existing AI work on modelling legal reasoning with evidence.

The paper has been awarded the Don Berman Award for Best Student Paper at the 11th International Conference on Artificial Intelligence and Law (ICAIL 2007).

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Reference:
Bex, F. J., Prakken, H., & Verheij, B. (2007). Formalising Argumentative Story-based Analysis of Evidence. The 11th International Conference on Artificial Intelligence and Law. Proceedings of the Conference, 1-10. New York (New York): ACM.

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