AcbAr - Atomic-based Argumentation Solver

Tuomo Lehtonen; Anna Rapberger; Markus Ulbricht; Johannes Peter Wallner

AcbAr - Atomic-based Argumentation Solver

Tuomo Lehtonen, Anna Rapberger, Markus Ulbricht, Johannes Peter Wallner

Institute of Software Engineering and Artificial Intelligence (7160)

Publikation: Andere Beiträge › Sonstiger Beitrag

Abstract

AcbAr is a solver for credulous and skeptical acceptance and finding extensions in Assumption-based Argumentation (ABA). AcbAr makes use of a recently introduced procedure to construct an abstract argumentation framework (AF) from ABA frameworks such that, unlike when using a conventional argument construction method, the size of the AF is polynomially bounded. The state-of-the-art SAT-based AF solver mu-toksia is used on the resulting AF to obtain answers to the reasoning tasks. AcbAr participates in all ABA subtracks of ICCMA 2023, namely DC-CO, DC-ST, DS-ST, DS-PR, SE-ST and SE-PR.

Originalsprache	englisch
Seitenumfang	2
Publikationsstatus	Veröffentlicht - 2023

Zugriff auf Dokument

https://hdl.handle.net/10138/565357

Andere Dateien und Links

https://bitbucket.org/lehtonen/acbar/src/master/

1 Laufend

FWF - Neue KI - Neue Berechnungsmethoden für Argumentationsmodelle in der KI
Wallner, J. P. (Teilnehmer (Co-Investigator))
1/09/22 → 31/08/25
Projekt: Forschungsprojekt

1 Beitrag in einem Konferenzband

Argumentation Frameworks induced by Assumption-based Argumentation: Relating Size and Complexity
Lehtonen, T., Rapberger, A., Ulbricht, M. & Wallner, J. P., 2023, Proceedings KR. Marquis, P., Son, T. C. & Kern-Isberner, G. (Hrsg.). ijcai.org, S. 440-450 11 S.
Publikation: Beitrag in Buch/Bericht/Konferenzband › Beitrag in einem Konferenzband › Begutachtung

Open Access
Datei

Dieses zitieren

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abstract = "AcbAr is a solver for credulous and skeptical acceptance and finding extensions in Assumption-based Argumentation (ABA). AcbAr makes use of a recently introduced procedure to construct an abstract argumentation framework (AF) from ABA frameworks such that, unlike when using a conventional argument construction method, the size of the AF is polynomially bounded. The state-of-the-art SAT-based AF solver mu-toksia is used on the resulting AF to obtain answers to the reasoning tasks. AcbAr participates in all ABA subtracks of ICCMA 2023, namely DC-CO, DC-ST, DS-ST, DS-PR, SE-ST and SE-PR.",

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T1 - AcbAr - Atomic-based Argumentation Solver

AU - Lehtonen, Tuomo

AU - Rapberger, Anna

AU - Ulbricht, Markus

AU - Wallner, Johannes Peter

PY - 2023

Y1 - 2023

N2 - AcbAr is a solver for credulous and skeptical acceptance and finding extensions in Assumption-based Argumentation (ABA). AcbAr makes use of a recently introduced procedure to construct an abstract argumentation framework (AF) from ABA frameworks such that, unlike when using a conventional argument construction method, the size of the AF is polynomially bounded. The state-of-the-art SAT-based AF solver mu-toksia is used on the resulting AF to obtain answers to the reasoning tasks. AcbAr participates in all ABA subtracks of ICCMA 2023, namely DC-CO, DC-ST, DS-ST, DS-PR, SE-ST and SE-PR.

AB - AcbAr is a solver for credulous and skeptical acceptance and finding extensions in Assumption-based Argumentation (ABA). AcbAr makes use of a recently introduced procedure to construct an abstract argumentation framework (AF) from ABA frameworks such that, unlike when using a conventional argument construction method, the size of the AF is polynomially bounded. The state-of-the-art SAT-based AF solver mu-toksia is used on the resulting AF to obtain answers to the reasoning tasks. AcbAr participates in all ABA subtracks of ICCMA 2023, namely DC-CO, DC-ST, DS-ST, DS-PR, SE-ST and SE-PR.

UR - https://bitbucket.org/lehtonen/acbar/src/master/

M3 - Other contribution

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AcbAr - Atomic-based Argumentation Solver

Abstract

Zugriff auf Dokument

Andere Dateien und Links

Fingerprint

Projekte

FWF - Neue KI - Neue Berechnungsmethoden für Argumentationsmodelle in der KI

Publikationen

Argumentation Frameworks induced by Assumption-based Argumentation: Relating Size and Complexity

Dieses zitieren