A Comparative Study of Ranking-Based Semantics for Abstract Argumentation

Authors: Elise Bonzon, Jérôme Delobelle, Sébastien Konieczny, Nicolas Maudet

AAAI 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical This is what we propose in this work. We provide a general comparison of all these semantics with respect to the proposed properties. That allows to underline the differences of behavior between the existing semantics.
Researcher Affiliation Academia Elise Bonzon LIPADE Universit e Paris Descartes France bonzon@parisdescartes.fr; J erˆome Delobelle CRIL, CNRS Universit e d Artois France delobelle@cril.fr; S ebastien Konieczny CRIL, CNRS Universit e d Artois France konieczny@cril.fr; Nicolas Maudet Sorbonne Universit es UPMC Univ Paris 06, CNRS LIP6, UMR 7606 75005 Paris nicolas.maudet@lip6.fr
Pseudocode Yes Algorithm 1: Tuples
Open Source Code No The paper does not provide any explicit statement about releasing source code for the comparative study or implementations of the semantics discussed, nor does it include a link to a code repository.
Open Datasets No The paper focuses on theoretical analysis of argumentation semantics and uses small, illustrative examples (like Example 1 with 5 arguments) rather than empirical evaluation on a dataset. No public dataset or access information for one is mentioned.
Dataset Splits No The paper focuses on theoretical analysis and does not involve empirical experiments with datasets. Therefore, there are no training, validation, or test splits described.
Hardware Specification No The paper is a theoretical comparative study and does not describe any computational experiments that would require specific hardware. Therefore, no hardware specifications are mentioned.
Software Dependencies No The paper is a theoretical comparative study and does not describe any computational experiments that would require specific software dependencies with version numbers.
Experiment Setup No The paper focuses on theoretical analysis of argumentation semantics and their properties. It does not describe any empirical experiments with specific setup details, hyperparameters, or training configurations.