Record link: 
http://hdl.handle.net/20.500.12708/192184
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Title: 
From Qualitative Choice Logic to Abstract Argumentation
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Citation: 
Bernreiter, M., & König, M. (2023). From Qualitative Choice Logic to Abstract Argumentation. In Proceedings of the Twentieth International Conference on Principles of Knowledge Representation and Reasoning (pp. 737–741). International Joint Conferences on Artificial Intelligence Organization. https://doi.org/10.24963/kr.2023/73
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Publisher DOI: 
10.24963/kr.2023/73
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Publication Type: 
Inproceedings - Full-Paper Contribution
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Language: 
English
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Authors: 
Bernreiter, Michael 
König, Matthias 
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Organisational Unit: 
E192-02 - Forschungsbereich Databases and Artificial Intelligence 
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Published in: 
Proceedings of the Twentieth International Conference on Principles of Knowledge Representation and Reasoning 
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ISBN: 
9781956792027
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Volume: 
KR-2023
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DOI of the book: 
10.24963/kr.2023
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Date (published): 
15-Sep-2023
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Event name: 
20th International Conference on Principles of Knowledge Representation and Reasoning, KR 2023 
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Event date: 
2-Sep-2023 - 8-Sep-2023
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Event place: 
Rhodos, Greece
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Number of Pages: 
5
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Publisher: 
International Joint Conferences on Artificial Intelligence Organization
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Peer reviewed: 
Yes
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Keywords: 
Qualitative Choice Logic (QCL); Argumentation; Argumentation Frameworks; Collective Attacks; Encoding QCL-formulas; Capturing Preferred Models
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Abstract: 
Qualitative Choice Logic (QCL) extends classical proposi- tional formulas by a connective called ordered disjunction that is used to express preferences. We translate QCL the- ories to Argumentation Frameworks with Collective Attacks (SETAFs), and show that the preferred models of the origi- nal theory directly correspond to the semi-stable extensions of the target framework. This further allows us to decide the problem of preferred model entailment for QCL via SETAFs.
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Project title: 
Hybrid Parameterized Problem Solving in Practice: P32830-N (FWF - Österr. Wissenschaftsfonds) 
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Research Areas: 
Logic and Computation: 100%
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Science Branch: 
1020 - Informatik: 80%
1010 - Mathematik: 20%
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Appears in Collections:
Conference Paper

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