Toward incremental computation of argumentation semantics: A decomposition-based approach

  • Authors:

  • Beishui Liao

  • Affiliations:

  • Center for the Study of Language and Cognition, Department of Philosophy, Zhejiang University, Hangzhou, China 310028

  • Venue:
  • Annals of Mathematics and Artificial Intelligence
  • Year:
  • 2013

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Abstract

Currently, except some classes of argumentation frameworks (with special topologies or fixed parameters, such as acyclic, symmetric, and bounded tree-width, etc.) that have been clearly identified as tractable, for a generic argumentation framework (also called a defeat graph), how to efficiently compute its semantics is still a challenging problem. Inspired by the local tractability of an argumentation framework, we first propose a decomposition-based approach, and then conduct an empirical investigation. Given a generic argumentation framework, it is firstly decomposed into a set of sub-frameworks that are located in a number of layers. Then, the semantics of an argumentation framework are computed incrementally, from the lowest layer in which each sub-framework is not restricted by other sub-frameworks, to the highest layer in which each sub-framework is most restricted by the sub-frameworks located in the lower layers. In each iteration, the semantics of each sub-framework is computed locally, while the combination of semantics of a set of sub-frameworks is performed in two dimensions: horizontally and vertically. The average results show that when the ratio of the number of edges to the number of nodes of a defeat graph is less than 1.5:1, the decomposition-based approach is obviously efficient.