<div class="csl-bib-body">
<div class="csl-entry">Linsbichler, T., Maratea, M., Niskanen, A., Wallner, J. P., & Woltran, S. (2022). Advanced algorithms for abstract dialectical frameworks based on complexity analysis of subclasses and SAT solving. <i>Artificial Intelligence</i>, <i>307</i>, 1–40. https://doi.org/10.1016/j.artint.2022.103697</div>
</div>
-
dc.identifier.issn
0004-3702
-
dc.identifier.uri
http://hdl.handle.net/20.500.12708/139733
-
dc.description.abstract
Abstract dialectical frameworks (ADFs) constitute one of the most powerful formalisms in abstract argumentation. Their high computational complexity poses, however, certain challenges when designing efficient systems. In this paper, we tackle this issue by (i) analyzing the complexity of ADFs under structural restrictions, (ii) presenting novel algorithms which make use of these insights, and (iii) implementing these algorithms via (multiple) calls to SAT solvers. An empirical evaluation of the resulting implementation on ADF benchmarks generated from ICCMA competitions shows that our solver is able to outperform state-of-the-art ADF systems.
en
dc.description.sponsorship
Fonds zur Förderung der wissenschaftlichen Forschung (FWF)
-
dc.language.iso
en
-
dc.publisher
Elsevier
-
dc.relation.ispartof
Artificial Intelligence
-
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
-
dc.subject
Abstract dialectical frameworks
en
dc.subject
Complexity analysis
en
dc.subject
SAT-based procedures
en
dc.title
Advanced algorithms for abstract dialectical frameworks based on complexity analysis of subclasses and SAT solving
