Implementing Explanation-Based Argumentation using Answer Set Programming

This paper presents an implementation for an explanation-based theory of argumentation. Instead of referring to attack/support relationships between arguments, as in traditional argumentation theories, we focus on the relation of messages with the space of hypothetical explanations. The consequences of this choice are two-fold. First, attack and support relationships become derivative measures. Second, we unveil a natural integration with probabilistic reasoning. The proposed operationalization is based on stable models semantics for logic programming