The Effect of Preferences in Abstract Argumentation under a Claim-Centric View
Authors: Michael Bernreiter, Wolfgang Dvorak, Anna Rapberger, Stefan Woltran
AAAI 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this paper, we study the effect of preferences in abstract argumentation under a claim-centric perspective. Our main contributions are as follows: For each of the four reductions, we characterize the possible structure of CAFs that are obtained by applying the reduction to a well-formed CAF and a preference relation. We investigate the relationship between these classes. We study I-maximality of stable, preferred, semi-stable, stage, and naive semantics of the novel CAF classes. Finally, we investigate the complexity of reasoning for CAFs with preferences with respect to conflict-free, admissible, complete, and all of the aforementioned semantics. |
| Researcher Affiliation | Academia | Michael Bernreiter, Wolfgang Dvoˇr ak, Anna Rapberger, Stefan Woltran Institute of Logic and Computation, TU Wien, Austria {mbernrei,dvorak,arapberg,woltran}@dbai.tuwien.ac.at |
| Pseudocode | No | The paper does not contain structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide concrete access to source code. It is a theoretical paper and does not mention any code release. |
| Open Datasets | No | The paper does not describe experiments using datasets, thus no information on public dataset availability is provided. |
| Dataset Splits | No | The paper does not describe experiments using datasets, thus no information on dataset splits for validation is provided. |
| Hardware Specification | No | The paper is theoretical and does not describe any experimental setup or hardware used. |
| Software Dependencies | No | The paper is theoretical and does not describe any experimental setup or specific software dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical and does not describe any experimental setup details such as hyperparameters or training configurations. |