Inconsistency Handling in DatalogMTL

Inconsistency Handling in DatalogMTL

Meghyn Bienvenu, Camille Bourgaux, Atefe Khodadaditaghanaki

Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence
Main Track. Pages 4374-4381. https://doi.org/10.24963/ijcai.2025/487

In this paper, we explore the issue of inconsistency handling in DatalogMTL, an extension of Datalog with metric temporal operators. Since facts are associated with time intervals, there are different manners to restore consistency when they contradict the rules, such as removing facts or modifying their time intervals. Our first contribution is the definition of relevant notions of conflicts (minimal explanations for inconsistency) and repairs (possible ways of restoring consistency) for this setting and the study of the properties of these notions and the associated inconsistency-tolerant semantics. Our second contribution is a data complexity analysis of the tasks of generating a single conflict / repair and query entailment under repair-based semantics.
Keywords:
Knowledge Representation and Reasoning: KRR: Qualitative, geometric, spatial, and temporal reasoning
Knowledge Representation and Reasoning: KRR: Computational complexity of reasoning
Knowledge Representation and Reasoning: KRR: Non-monotonic reasoning