Extending Labelling Semantics to Weighted Argumentation Frameworks

Authors

  • Carlo Taticchi Gran Sasso Science Institute
  • Stefano Bistarelli

DOI:

https://doi.org/10.32473/flairs.v34i1.128346

Keywords:

argumentation theory, labelling-based semantics, weighted argumentation framework

Abstract

Argumentation Theory provides tools for both modelling and reasoning with controversial information and is a methodology that is often used as a way to give explanations to results provided using machine learning techniques. In this context, labelling-based semantics for Abstract Argumentation Frameworks (AFs) allow for establishing the acceptability of sets of arguments, dividing them into three partitions: acceptable, rejected and undecidable (instead of classical Dung two sets IN and OUT partitions). This kind of semantics have been studied only for classical AFs, whilst the more powerful weighted and preference-based framework has been not studied yet. In this paper, we define a novel labelling semantics for Weighted Argumentation Frameworks, extending and generalising the crisp one.

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Published

2021-04-18

How to Cite

Taticchi, C., & Bistarelli, S. (2021). Extending Labelling Semantics to Weighted Argumentation Frameworks. The International FLAIRS Conference Proceedings, 34. https://doi.org/10.32473/flairs.v34i1.128346

Issue

Section

Special Track: Uncertain Reasoning