Taking the dialectical stance in reasoning with evidence and proof

We present a computational argumentation approach that models legal reasoning with evidence and proof as dialectical rather than probabilistic. This hybrid approach of stories and arguments models the process of proof in a way that is compatible with Allen and Pardo's theory of relative plausibility by adding arguments that can be used to show how evidence can support or attack explanations. Using some legal cases as examples, we show how criteria for assessing explanations connect arguments and evidence to story schemes. We show how this hybrid dialectical approach avoids the main problem of the probabilistic approaches, namely that they require precise numbers to be applied in order to decide legal cases. We provide an alternative method that allows fact-finders to reason with evidence holistically and not in the item-by-item fashion proposed by the probabilistic account