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Applying automated reasoning tools for decision support and analysis in lawhas the potential to make court decisions more transparent and objective. Sincethere is often uncertainty about the accuracy and relevance of evidence,non-classical reasoning approaches are required. Here, we investigateprobabilistic epistemic argumentation as a tool for automated reasoning aboutlegal cases. We introduce a general scheme to model legal cases asprobabilistic epistemic argumentation problems, explain how evidence can bemodeled and sketch how explanations for legal decisions can be generatedautomatically. Our framework is easily interpretable, can deal with cyclicstructures and imprecise probabilities and guarantees polynomial-timeprobabilistic reasoning in the worst-case.

Explainable Automated Reasoning in Law using Probabilistic Epistemic Argumentation