Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in [1].
Dung’s Argumentation Framework: Unveiling the Expressive Power with Inconsistent Databases
Authors: Yasir Mahmood, Markus Hecher, Axel-Cyrille Ngonga Ngomo
AAAI 2025 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | Our main contributions include translating an argumentation framework into a database together with integrity constraints. Moreover, this translation can be achieved in polynomial time, which is essential in transferring complexity results between the two formalisms. Contributions. Proof details (marked with ) are available online (Mahmood, Hecher, and Ngomo 2024). In details, we establish the following (see Table 1 for an overview). We present a database view for Dung s theory of argumentation and prove that an AF can be seen as an inconsistent database in the presence of functional and inclusion dependencies. This also establishes the exact expressive power of AFs in terms of integrity constraints. We prove that the extensions of an AF correspond precisely to the subset-repairs of the resulting database for conflict-free, admissible, naive and preferred semantics. |
| Researcher Affiliation | Academia | 1DICE group, Department of Computer Science, Paderborn University, Germany 2Univ. Artois, CNRS, UMR 8188, Centre de Recherche en Informatique de Lens (CRIL), F-62300 Lens, France 3CSAIL, Massachusetts Institute of Technology, United States |
| Pseudocode | No | The paper defines formal concepts and presents theorems and proofs. It describes methods in narrative text and formal notation but does not include any clearly labeled pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide any explicit statements about the release of source code for the methodology described, nor does it include links to code repositories. |
| Open Datasets | No | The paper focuses on theoretical contributions regarding argumentation frameworks and inconsistent databases. It does not utilize any datasets for empirical evaluation, hence no information about open datasets is provided. |
| Dataset Splits | No | The paper is theoretical and does not involve experimental evaluation using datasets, therefore, there is no mention of dataset splits. |
| Hardware Specification | No | The paper presents theoretical work on formalisms and does not describe any experimental setup that would require specific hardware. Thus, no hardware specifications are mentioned. |
| Software Dependencies | No | The paper is theoretical and does not describe any computational experiments or implementations that would necessitate detailing specific software dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical, presenting proofs and formal connections between concepts. It does not include any experimental setup details, hyperparameter values, or training configurations. |