ConArgLib: an argumentation library with support to search strategies and parallel search. Issue 6 (2nd November 2021)

• Record Type: Journal Article
• Authors: Bistarelli, Stefano; Rossi, Fabio; Santini, Francesco
• Is Part Of: Journal of experimental & theoretical artificial intelligence. Volume 33:Issue 6(2021)
• Page Start: 891
• Page End: 918
• Publication Date: 2021-11-02
• Subjects: Abstract Argumentation -- solver -- weighted edges -- constraint programming; Artificial intelligence -- Periodicals; 006.3
• DOI: 10.1080/0952813X.2020.1789756
• Languages: English
• ISSNs: 0952-813X

Abstract

ABSTRACT: We present ConArgLib, a C++ library implemented to help programmers solve some of the most important problems related to extension-based abstract Argumentation. The library is based on ConArg, which exploits Constraint Programming and, in particular, Gecode, a toolkit for developing constraint-based systems and applications. Given a semantics, such problems consist, for example, in enumerating all the extensions, and checking the credulous or sceptical acceptance of an argument passed as parameter. The goal is to let programmers use the library to quickly develop programs on top of it, as, for instance, implementing decision-making procedures based on the strongest arguments, or comparing two frameworks by looking at the differences between their (e.g., stable) semantics. The library features the possibility to use different branching strategies, which we all test and compare on a set of frameworks taken from the International Competition on Computational Models of Argumentation ( ICCMA17 ). Moreover, for some of the tasks, it is possible to perform a parallel search using several workers at the same time: we test the speed-up between using from 1 to 16 threads on a set of ICCMA17 frameworks.