Explainable Automated Reasoning in Law using Probabilistic Epistemic\n Argumentation

Applying automated reasoning tools for decision support and analysis in law\nhas the potential to make court decisions more transparent and objective. Since\nthere is often uncertainty about the accuracy and relevance of evidence,\nnon-classical reasoning approaches are required. Here, we investigate\nprobabilistic epistemic argumentation as a tool for automated reasoning about\nlegal cases. We introduce a general scheme to model legal cases as\nprobabilistic epistemic argumentation problems, explain how evidence can be\nmodeled and sketch how explanations for legal decisions can be generated\nautomatically. Our framework is easily interpretable, can deal with cyclic\nstructures and imprecise probabilities and guarantees polynomial-time\nprobabilistic reasoning in the worst-case.\n