A Labelling Framework for Probabilistic Argumentation
This work addresses the need for a unified framework in probabilistic argumentation for researchers and practitioners dealing with qualitative and quantitative uncertainty, though it appears incremental as it builds on existing structured and abstract argumentation methods.
The authors tackled the problem of diverse and fragmented approaches to probabilistic argumentation by proposing a general labelling-oriented framework that systematically handles multiple types of uncertainty, such as credibility of premises and acceptance status of arguments, and used it to evaluate existing literature claims.
The combination of argumentation and probability paves the way to new accounts of qualitative and quantitative uncertainty, thereby offering new theoretical and applicative opportunities. Due to a variety of interests, probabilistic argumentation is approached in the literature with different frameworks, pertaining to structured and abstract argumentation, and with respect to diverse types of uncertainty, in particular the uncertainty on the credibility of the premises, the uncertainty about which arguments to consider, and the uncertainty on the acceptance status of arguments or statements. Towards a general framework for probabilistic argumentation, we investigate a labelling-oriented framework encompassing a basic setting for rule-based argumentation and its (semi-) abstract account, along with diverse types of uncertainty. Our framework provides a systematic treatment of various kinds of uncertainty and of their relationships and allows us to back or question assertions from the literature.