Work

Capturing Non-flat Assumption-based Argumentation with Bipolar SETAFs

Year: 2024

Type: conference-paper

Abstract: While the flat fragment of assumption-based argumentation (ABA) is widely studied in the literature, the general, non-flat case has mostly been neglected so far. Until recently, there was no possible way to instantiate non-flat ABA in terms of an abstract argumentation framework. While this gap has been closed for complete-based ABA semantics, capturing admissible-based semantics cannot yet be achieved by looking at the relation between the instantiated arguments only; it requires augmenting arguments with their premises, hence being a semi-abstract instantiaiton. In this paper, we provide a compact and fully abstract instantiation by making use of both collective attack and support relations. Then, inspired by fundamental properties of abstract formalisms, we identify flaws of native ABA semantics in the non-flat case and provide refinements thereof, utilizing our novel instatiation.

DOI: 10.24963/kr.2024/12

Authors: Matti Berthold, Anna Rapberger, Markus Ulbricht

Institutions: Center for Scalable Data Analytics and Artificial Intelligence, Leipzig University, Imperial College London

Language: English

Topic: Multi-Agent Systems and Negotiation

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Funders: European Commission, Bundesministerium für Bildung und Forschung

Awards: G4186543413, G434337789

OpenAlex ID: W4403792969