An efficient java-based solver for abstract argumentation frameworks: jArgSemSAT

Cerutti, Federico ORCID: https://orcid.org/0000-0003-0755-0358, Vallati, Mauro and Giacomin, Massimiliano 2017. An efficient java-based solver for abstract argumentation frameworks: jArgSemSAT. International Journal on Artificial Intelligence Tools 26 (2) , 1750002. 10.1142/S0218213017500026

Preview

PDF - Accepted Post-Print Version Download (482kB) | Preview

Abstract

Dung’s argumentation frameworks are adopted in a variety of applications, from argument-mining, to intelligence analysis and legal reasoning. Despite this broad spectrum of already existing applications, the mostly adopted solver—in virtue of its simplicity—is far from being comparable to the current state-of-the-art solvers. On the other hand, most of the current state-of-the-art solvers are far too complicated to be deployed in real-world settings. In this paper we provide and extensive description of jArgSemSAT, a Java re-implementation of ArgSemSAT. ArgSemSAT represents the best single solver for argumentation semantics with the highest level of computational complexity. We show that jArgSemSAT can be easily integrated in existing argumentation systems (1) as an off-the-shelf, standalone, library; (2) as a Tweety compatible library; and (3) as a fast and robust web service freely available on the Web. Our large experimental analysis shows that—despite being written in Java—jArgSemSAT would have scored in most of the cases among the three bests solvers for the two semantics with highest computational complexity—Stable and Preferred—in the last competition on computational models of argumentation.

Item Type:	Article
Date Type:	Published Online
Status:	Published
Schools:	Computer Science & Informatics
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Uncontrolled Keywords:	Abstract argumentation; argumentation semantics; off-the-shelf solver
Publisher:	World Scientific Publishing
ISSN:	0218-2130
Date of First Compliant Deposit:	22 September 2016
Date of Acceptance:	10 October 2016
Last Modified:	27 Nov 2024 16:15
URI:	https://orca.cardiff.ac.uk/id/eprint/94721

Citation Data

Cited 10 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item