# Towards Preserving Semantic Structure in Argumentative Multi-Agent via Abstract Interpretation

arXiv: https://arxiv.org/abs/2211.15782 · HTML: https://mlsanity.com/paper/2211.15782/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 19 references that are in the map.
- First posted on arXiv 28 Nov 2022.

## Builds on (most cited first, 1 of 1)

- [Explainability in autonomous pedagogically structured scenarios](https://mlsanity.com/paper/2210.12140/) (2022)

## Built on by (most cited first, 1 of 1)

- [Do intermediate feature coalitions aid explainability of black-box models?](https://mlsanity.com/paper/2303.11920/) (2023)

## Abstract (arXiv)

Over the recent twenty years, argumentation has received considerable attention in the fields of knowledge representation, reasoning, and multi-agent systems. However, argumentation in dynamic multi-agent systems encounters the problem of significant arguments generated by agents, which comes at the expense of representational complexity and computational cost. In this work, we aim to investigate the notion of abstraction from the model-checking perspective, where several arguments are trying to defend the same position from various points of view, thereby reducing the size of the argumentation framework whilst preserving the semantic flow structure in the system.