On Undisputed Sets in Abstract Argumentation

Authors: Matthias Thimm

AAAI 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical We investigate the properties of our new semantical notions and show certain relationships to classical semantics, in particular that undisputed sets are a generalisation of preferred extensions and strongly undisputed sets are a generalisation of stable extensions. We also investigate the computational complexity of standard reasoning tasks with these new notions and show that they lie on the second and third level of the polynomial hierarchy, respectively. Moreover, compared to weak admissibility-based semantics, where all reasoning problems are PSPACE-complete (Dvoˇr ak, Ulbricht, and Woltran 2021), our new semantical notions are significantly easier (under standard complexity-theoretic assumptions).
Researcher Affiliation Academia Matthias Thimm Artificial Intelligence Group, University of Hagen, Germany matthias.thimm@fernuni-hagen.de
Pseudocode No The paper does not contain any structured pseudocode or algorithm blocks.
Open Source Code No The paper does not provide an explicit statement about releasing source code for the described methodology or a link to a code repository.
Open Datasets No The paper is theoretical and uses small illustrative examples (e.g., AFs F0, F1, F2 in figures) rather than publicly available datasets for training or evaluation. No concrete access information for a dataset is provided.
Dataset Splits No The paper is theoretical and does not describe experiments involving data splits for training, validation, or testing.
Hardware Specification No The paper does not provide any specific details about the hardware (e.g., GPU/CPU models, memory) used for running any computations or analysis.
Software Dependencies No The paper does not list any specific software dependencies with version numbers.
Experiment Setup No The paper is theoretical and does not describe experiments that would require detailing a specific experimental setup or hyperparameters.