{"type":"ScholarlyArticle","title":"Decomposition-Guided Reductions for Argumentation and Treewidth","authors":[{"name":"Johannes Fichte","slug":"johannes-fichte","given":"Johannes","family":"Fichte","affiliation":""},{"name":"Markus Hecher","slug":"markus-hecher","given":"Markus","family":"Hecher","affiliation":""},{"name":"Yasir Mahmood","slug":"yasir-mahmood","given":"Yasir","family":"Mahmood","affiliation":""},{"name":"Arne Meier","slug":"arne-meier","given":"Arne","family":"Meier","affiliation":""}],"abstract":"Argumentation is a widely applied framework for modeling and evaluating arguments and its reasoning with various applications. Popular frameworks are abstract argumentation (Dung’s framework) or logic-based argumentation (Besnard-Hunter’s framework). Their computational complexity has been studied quite in-depth. Incorporating treewidth into the complexity analysis is particularly interesting, as solvers oftentimes employ SAT-based solvers, which can solve instances of low treewidth fast. In this paper, we address whether one can design reductions from argumentation problems to SAT-problems while linearly preserving the treewidth, which results in decomposition-guided (DG) reductions. It turns out that the linear treewidth overhead caused by our DG reductions, cannot be significantly improved under reasonable assumptions. Finally, we consider logic-based argumentation and establish new upper bounds using DG reductions and lower bounds.","doi":"10.24963/ijcai.2021/259","url":"https://ijcai.org/proceedings/2021/259","pdf":"https://ijcai.org/proceedings/2021/0259.pdf","markdown":"https://ijcai.org/proceedings/2021/259.md","bibtex":"https://ijcai.org/proceedings/2021/bibtex/259","volume":{"slug":"2021","title":"Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2021","url":"https://ijcai.org/proceedings/2021/","year":2021,"location":"Montreal","dates":"19-27 August 2021","editors":"Prof. Zhi-Hua Zhou","isbn":"978-0-9992411-9-6","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2021"},"section":"Knowledge Representation and Reasoning","track":"Main Track","number":259,"pages":{"first":1880,"last":1886},"keywords":["Knowledge Representation and Reasoning: Computational Models of Argument","Constraints and SAT: Constraint Satisfaction","Knowledge Representation and Reasoning: Computational Complexity of Reasoning"],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}