Ranking-Based Argumentation Semantics Applied to Logical Argumentation
Abstract
In formal argumentation, a distinction can be made between extension-based semantics, where sets of arguments are either (jointly) accepted or not, and ranking-based semantics, where grades of accept- ability are assigned to arguments. Another important distinction is that between abstract approaches, that abstract away from the content of arguments, and structured approaches, that specify a method of constructing argument graphs on the basis of a knowledge base. While ranking-based semantics have been extensively applied to abstract argumentation, few work has been done on ranking-based semantics for structured argumentation. In this paper, we make a systematic investigation into the be- haviour of ranking-based semantics applied to existing formalisms for structured argumentation. We show that a wide class of ranking-based semantics gives rise to so-called culpability measures, and are relatively robust to specific choices in argument construction methods.
Cite
Text
Heyninck et al. "Ranking-Based Argumentation Semantics Applied to Logical Argumentation." International Joint Conference on Artificial Intelligence, 2023. doi:10.24963/IJCAI.2023/364Markdown
[Heyninck et al. "Ranking-Based Argumentation Semantics Applied to Logical Argumentation." International Joint Conference on Artificial Intelligence, 2023.](https://mlanthology.org/ijcai/2023/heyninck2023ijcai-ranking/) doi:10.24963/IJCAI.2023/364BibTeX
@inproceedings{heyninck2023ijcai-ranking,
title = {{Ranking-Based Argumentation Semantics Applied to Logical Argumentation}},
author = {Heyninck, Jesse and Raddaoui, Badran and Straßer, Christian},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2023},
pages = {3268-3276},
doi = {10.24963/IJCAI.2023/364},
url = {https://mlanthology.org/ijcai/2023/heyninck2023ijcai-ranking/}
}