Dvořák, W., Hecher, M., König, M., Schidler, A., Szeider, S., & Woltran, S. (2022). Tractable Abstract Argumentation via Backdoor-Treewidth. In Proceedings of the 36th AAAI Conference on Artificial Intelligence (pp. 5608–5615). AAAI Press. https://doi.org/10.1609/aaai.v36i5.20501
E192-01 - Forschungsbereich Algorithms and Complexity E192-02 - Forschungsbereich Databases and Artificial Intelligence
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Published in:
Proceedings of the 36th AAAI Conference on Artificial Intelligence
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ISBN:
978-1-57735-876-3
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Volume:
36
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Date (published):
28-Jun-2022
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Event name:
AAAI 2022
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Event date:
22-Feb-2022 - 1-Mar-2022
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Event place:
Canada
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Number of Pages:
8
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Publisher:
AAAI Press, Palo Alto, California USA
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Peer reviewed:
Yes
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Keywords:
Knowledge Representation and Reasoning; Argumentation frameworks; backdoor-treewidth approach
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Abstract:
Argumentation frameworks (AFs) are a core formalism in the field of formal argumentation. As most standard computational tasks regarding AFs are hard for the first or second level of the Polynomial Hierarchy, a variety of algorithmic approaches to achieve manageable runtimes have been considered in the past. Among them, the backdoor-approach and the treewidth-approach turned out to yield fixed-parameter tractable fragments. However, many applications yield high parameter values for these methods, often rendering them infeasible in practice. We introduce the backdoor-treewidth approach for abstract argumentation, combining the best of both worlds with a guaranteed parameter value that does not exceed the minimum of the backdoor- and treewidth-parameter. In particular, we formally define backdoor-treewidth and establish fixed-parameter tractability for standard reasoning tasks of abstract argumentation. Moreover, we provide systems to find and exploit backdoors of small width, and conduct systematic experiments evaluating the new parameter.
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Project title:
Revealing and Utilizing the Hidden Structure for Solving Hard Problems in AI: ICT19-065 (WWTF Wiener Wissenschafts-, Forschu und Technologiefonds) Extending Methods in Belief Change for a Principled Approach to Advance Dynamics in Argumentation: P30168-N31 (FWF Fonds zur Förderung der wissenschaftlichen Forschung (FWF)) SAT-Basierende lokale Verbesserungsmethoden: P32441-N35 (FWF Fonds zur Förderung der wissenschaftlichen Forschung (FWF)) Hybrid Parameterized Problem Solving in Practice: P32830-N (FWF Fonds zur Förderung der wissenschaftlichen Forschung (FWF))
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Project (external):
Austrian Science Fund (FWF) Austrian Science Fund (FWF)