Computing stable and preferred extensions of dynamic bipolar argumentation frameworks

Bipolar argumentation frameworks (BAFs) extend Dung's argumentation frameworks to explicitly represent the notion of support between arguments, in addition to that of attack. BAFs can be profitably used to model disputes between two or more agents, with the aim of deciding the sets of arguments that should be accepted to support a point of view in a discussion. However, since new arguments, attacks, and supports are often introduced to take into account new available knowledge, BAFs as well as the set of accepted arguments (under a given semantics) change over the time. In this paper we tackle the problem of efficiently recomputing sets of accepted arguments of dynamic BAFs (under the preferred and stable semantics). In particular, focusing on a deductive interpretation of support, we introduce an incremental algorithm that, given an initial BAF, an initial extension for it, and an update, computes an extension of the updated BAF. The experiments show that our technique is faster than computing an extension of the updated BAF from scratch.