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河北工业大学

An Efficient Java-Based Solver for Abstract Argumentation Frameworks: jArgSemSAT.

Title: An Efficient Java-Based Solver for Abstract Argumentation Frameworks: jArgSemSAT.
Authors: Cerutti, Federico1
Vallati, Mauro2
Giacomin, Massimiliano3
Source: International Journal on Artificial Intelligence Tools. Apr2017, Vol. 26 Issue 2, p-1. 26p.
Document Type: Article
Subject Terms: ARTIFICIAL intelligence
SEMANTIC integration (Computer systems)
JAVA (Computer program language)
Author-Supplied Keywords: Abstract argumentation ; argumentation semantics ; off-the-shelf solver
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. [ABSTRACT FROM AUTHOR]
(Copyright applies to all Abstracts.)
Author Affiliations: 1S0218213017500026AF001 ; 2S0218213017500026AF002 ; 3S0218213017500026AF003
ISSN: 0218-2130 (Sherpa/RoMEO, JCR)
PageCount: -1-25
volume: 26
issue: 2
issn: 02182130
pubdate: 2017
DOI: https://doi.org/10.1142/S0218213017500026
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