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Characterizing conflict-free and naive labellings—realizabiliy, uniqueness and patterns of redundancy

Published online by Cambridge University Press:  05 December 2025

Ringo Baumann
Affiliation:
Computer Science Institute, Leipzig University , Leipzig, Germany Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI) Dresden/Leipzig, Leipzig University, Leipzig, Germany
Anne-Marie Heine*
Affiliation:
Computer Science Institute, Leipzig University , Leipzig, Germany Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI) Dresden/Leipzig, Leipzig University, Leipzig, Germany
*
Corresponding author: Anne-Marie Heine; Email: aheine@informatik.uni-leipzig.de
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Abstract

The article is concerned with realizability in abstract argumentation. It provides characterization theorems for the most basic types of labelling-based semantics, namely conflict-free and naive labellings. It turns out that existing characterizations for extension-based semantics are of little help in characterizing labelling-based semantics. To this end, we introduce several new criteria like L-tightness, reject-witnessing, reject-compositionality as well as the new construct of a labelling-downward-closure, which help determine whether a given set of labellings is realizable regarding conflict-free or naive semantics. Moreover, we present standard constructions and analyse their uniqueness status. Further classical concepts like ordinary and strong equivalence are studied too. Last but not least, we delve into the characterization of stable labellings. It turns out that this endeavour is a highly non-trivial task with many parallels to so-called compact realizability, an open problem for stable semantics in abstract argumentation.

Information

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2025. Published by Cambridge University Press
Figure 0

Figure 1. Tables Example 13.