A survey of uncertainties and their consequences in probabilistic legal argumentation

In this chapter, we present a survey of different sorts of uncertainties lawyers reason with and connect them to the issue of how probabilistic models of argumentation can facilitate litigation planning. We briefly survey Bayesian Networks as a representation for argumentation in the context of a realistic example. After introducing the Carneades argument model and its probabilistic semantics, we propose an extension to the Carneades Bayesian Network model to support probability distributions over argument weights, a feature we believe is desirable. Finally, we scout possible future approaches to facilitate reasoning with argument weights.