---
title: "Robustness in Single-Audience Value-based Abstract Argumentation: Complexity Results"
authors:
  - "Bettina Fazzinga"
  - "Sergio Flesca"
  - "Filippo Furfaro"
doi: "10.24963/ijcai.2025/499"
url: "https://ijcai.org/proceedings/2025/499"
pdf: "https://ijcai.org/proceedings/2025/0499.pdf"
venue: "Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence"
year: 2025
pages: "4482-4490"
track: "Main Track"
keywords:
  - "Knowledge Representation and Reasoning: KRR: Computational complexity of reasoning"
  - "Knowledge Representation and Reasoning: KRR: Argumentation"
---

# Robustness in Single-Audience Value-based Abstract Argumentation: Complexity Results

Bettina Fazzinga, Sergio Flesca, Filippo Furfaro

*Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence*, pages 4482-4490. DOI: [10.24963/ijcai.2025/499](https://doi.org/10.24963/ijcai.2025/499)

## Abstract

We address the context of Single-Audience Value-Based Abstract Argumentation Framework (AVAF),
where the arguments are labeled with the social values that they promote and 
the activation/deactivation of the attacks depends on the audience profile
(expressed as a set of preferences between the social values).
Herein, we introduce a new notion of robustness for measuring the sensitivity of the outcome of the reasoning to the extent of changes in the audience profile. 
In particular, for a set of arguments S or a single argument a, we define the robustness degree
of the status of S or a as the maximum number k* of  deletions/insertions of preferences 
from/into the audience profile that are tolerable, in the sense that S remains an extension 
(or a non-extension) or a accepted (or unaccepted) after performing at most k* deletions/insertions.
We introduce the decision problems related to the computation of the robustness degree and focus on thoroughly investigating their computational complexity.