Pruning Search Space in Defeasible Argumentation
  Defeasible argumentation has experienced a considerable growth in AI in the
last decade. Theoretical results have been combined with development of
practical applications in AI & Law, Case-Based Reasoning and various
knowledge-based systems. However, the dialectical process associated with
inference is computationally expensive. This paper focuses on speeding up this
inference process by pruning the involved search space. Our approach is
twofold. On one hand, we identify distinguished literals for computing defeat.
On the other hand, we restrict ourselves to a subset of all possible
conflicting arguments by introducing dialectical constraints.
