An Extension-Based Argument-Ranking Semantics: Social Rankings in Abstract Argumentation
Authors: Lars Bengel, Giovanni Buraglio, Jan Maly, Kenneth Skiba
AAAI 2025 | Venue PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this paper, we introduce a new family of argument-ranking semantics which can be seen as a refinement of the classification of arguments into skeptically accepted, credulously accepted and rejected. To this end we use so-called social ranking functions which have been developed recently to rank individuals based on their performance in groups. We provide necessary and sufficient conditions for a social ranking function to give rise to an argument-ranking semantics satisfying the desired refinement property. ... More generally, we show which axiomatic properties are sufficient and necessary for a social ranking operator to give rise to such a ranking (Section 4). Additionally, we show that the argument-ranking semantics induced by the lexicographic excellence operator satisfies these properties and is thus an example of an argument-ranking semantics that satisfies our refinement property. |
| Researcher Affiliation | Academia | 1Artificial Intelligence Group, University of Hagen, Hagen, Germany 2Institute of Logic and Computation, TU Wien, Wien, Austria 3Institute of Data, Process and Knowledge Management, WU Vienna University of Economics and Business, Wien, Austria EMAIL, EMAIL, EMAIL, EMAIL |
| Pseudocode | No | The paper defines concepts, theorems, and provides examples, but does not include any explicitly labeled pseudocode or algorithm blocks. The methodologies are described in prose and mathematical definitions. |
| Open Source Code | No | The paper does not contain any explicit statements about releasing source code for the described methodology, nor does it provide links to any code repositories. It mentions 'Omitted proofs can be found in (Bengel et al. 2024).' referring to a long version of the paper, not code. |
| Open Datasets | No | This paper is theoretical in nature and does not describe experiments that utilize datasets. Therefore, no information about public dataset access is provided. |
| Dataset Splits | No | This paper is theoretical and does not involve experimental evaluation on datasets, thus no dataset split information is present. |
| Hardware Specification | No | The paper focuses on theoretical contributions in abstract argumentation and social ranking functions. It does not describe any experimental setup or the specific hardware used to run experiments. |
| Software Dependencies | No | The paper is theoretical and does not mention any specific software dependencies or versions required to implement or reproduce the described concepts. There are no practical implementations detailed. |
| Experiment Setup | No | The paper is theoretical and does not include an experimental setup section. It focuses on defining new semantics, properties, and theorems, without describing practical experiments, hyperparameters, or training configurations. |