Revisiting the Foundations of Abstract Argumentation – Semantics Based on Weak Admissibility and Weak Defense

Authors

  • Ringo Baumann Leipzig University
  • Gerhard Brewka Leipzig University
  • Markus Ulbricht Leipzig University

DOI:

https://doi.org/10.1609/aaai.v34i03.5661

Abstract

In his seminal 1995 paper, Dung paved the way for abstract argumentation, a by now major research area in knowledge representation. He pointed out that there is a problematic issue with self-defeating arguments underlying all traditional semantics. A self-defeat occurs if an argument attacks itself either directly or indirectly via an odd attack loop, unless the loop is broken up by some argument attacking the loop from outside. Motivated by the fact that such arguments represent self-contradictory or paradoxical arguments, he asked for reasonable semantics which overcome the problem that such arguments may indeed invalidate any argument they attack. This paper tackles this problem from scratch. More precisely, instead of continuing to use previous concepts defined by Dung we provide new foundations for abstract argumentation, so-called weak admissibility and weak defense. After showing that these key concepts are compatible as in the classical case we introduce new versions of the classical Dung-style semantics including complete, preferred and grounded semantics. We provide a rigorous study of these new concepts including interrelationships as well as the relations to their Dung-style counterparts. The newly introduced semantics overcome the issue with self-defeating arguments, and they are semantically insensitive to syntactic deletions of self-attacking arguments, a special case of self-defeat.

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Published

2020-04-03

How to Cite

Baumann, R., Brewka, G., & Ulbricht, M. (2020). Revisiting the Foundations of Abstract Argumentation – Semantics Based on Weak Admissibility and Weak Defense. Proceedings of the AAAI Conference on Artificial Intelligence, 34(03), 2742-2749. https://doi.org/10.1609/aaai.v34i03.5661

Issue

Section

AAAI Technical Track: Knowledge Representation and Reasoning