Grounding Rule-Based Argumentation Using Datalog
Aus International Center for Computational Logic
Grounding Rule-Based Argumentation Using Datalog
Martin DillerMartin Diller, Sarah Alice GagglSarah Alice Gaggl, Philipp HanischPhilipp Hanisch, Giuseppina MonterossoGiuseppina Monterosso, Fritz RauschenbachFritz Rauschenbach
Martin Diller, Sarah Alice Gaggl, Philipp Hanisch, Giuseppina Monterosso, Fritz Rauschenbach
Grounding Rule-Based Argumentation Using Datalog
In Magdalena Ortiz, Renata Wassermann, Torsten Schaub, eds., Proceedings of the 22nd International Conference on Principles of Knowledge Representation and Reasoning (KR 2025), 281–292, November 2025. IJCAI Organization
Grounding Rule-Based Argumentation Using Datalog
In Magdalena Ortiz, Renata Wassermann, Torsten Schaub, eds., Proceedings of the 22nd International Conference on Principles of Knowledge Representation and Reasoning (KR 2025), 281–292, November 2025. IJCAI Organization
- KurzfassungAbstract
ASPIC+ is one of the main general frameworks for rule-based argumentation for AI. Although first-order rules are commonly used in ASPIC+ examples, most existing approaches to reason over rule-based argumentation only support propositional rules. To enable reasoning over first-order instances, a preliminary grounding step is required. As groundings can lead to an exponential increase in the size of the input theories, intelligent procedures are needed. However, there is a lack of dedicated solutions for ASPIC+. Therefore, we propose an intelligent grounding procedure that keeps the size of the grounding manageable while preserving the correctness of the reasoning process. To this end, we translate the first-order ASPIC+ instance into a Datalog program and query a Datalog engine to obtain ground substitutions to perform the grounding of rules and contraries. Additionally, we propose simplifications specific to the ASPIC+ formalism to avoid grounding of rules that have no influence on the reasoning process. Finally, we performed an empirical evaluation of a prototypical implementation to show scalability. - Projekt:Project: SECAI, SEMECO-Q2
- Forschungsgruppe:Research Group: Logische Programmierung und ArgumentationLogic Programming and Argumentation, Wissensbasierte SystemeKnowledge-Based Systems
@inproceedings{DGHMR2025,
author = {Martin Diller and Sarah Alice Gaggl and Philipp Hanisch and
Giuseppina Monterosso and Fritz Rauschenbach},
title = {Grounding Rule-Based Argumentation Using Datalog},
editor = {Magdalena Ortiz and Renata Wassermann and Torsten Schaub},
booktitle = {Proceedings of the 22nd International Conference on Principles of
Knowledge Representation and Reasoning (KR 2025)},
publisher = {IJCAI Organization},
year = {2025},
month = {November},
pages = {281{\textendash}292},
doi = {https://doi.org/10.24963/kr.2025/28}
}