Grounding Rule-Based Argumentation Using Datalog

Fuente: arXiv
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Main Authors: Diller, Martin, Gaggl, Sarah Alice, Hanisch, Philipp, Monterosso, Giuseppina, Rauschenbach, Fritz
Format: Preprint
Published: 2025
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author Diller, Martin
Gaggl, Sarah Alice
Hanisch, Philipp
Monterosso, Giuseppina
Rauschenbach, Fritz
author_facet Diller, Martin
Gaggl, Sarah Alice
Hanisch, Philipp
Monterosso, Giuseppina
Rauschenbach, Fritz
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2508_10976
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Grounding Rule-Based Argumentation Using Datalog
Diller, Martin
Gaggl, Sarah Alice
Hanisch, Philipp
Monterosso, Giuseppina
Rauschenbach, Fritz
Artificial Intelligence
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.
title Grounding Rule-Based Argumentation Using Datalog
topic Artificial Intelligence
url https://arxiv.org/abs/2508.10976