Goal-Driven Reasoning in DatalogMTL with Magic Sets
Shaoyu Wang, Kaiyue Zhao, Dongliang Wei, Przemysław Andrzej Wałęga, Dingmin Wang, Hongming Cai, Pan Hu
Abstract
DatalogMTL is a powerful rule-based language for temporal reasoning. Due to its high expressive power and flexible modeling capabilities, it is suitable for a wide range of applications, including tasks from industrial and financial sectors. However, due its high computational complexity, practical reasoning in DatalogMTL is highly challenging. To address this difficulty, we introduce a new reasoning method for DatalogMTL which exploits the magic sets technique—a rewriting approach developed for (non-temporal) Datalog to simulate top-down evaluation with bottom-up reasoning. We have implemented this approach and evaluated it on publicly available benchmarks, showing that the proposed approach significantly and consistently outperformed state-of-the-art reasoning techniques.
BibTeX
@article{Wang_Zhao_Wei_Wałęga_Wang_Cai_Hu_2025, title={Goal-Driven Reasoning in DatalogMTL with Magic Sets}, volume={39}, url={https://ojs.aaai.org/index.php/AAAI/article/view/33668}, DOI={10.1609/aaai.v39i14.33668}, abstractNote={DatalogMTL is a powerful rule-based language for temporal reasoning. Due to its high expressive power and flexible modeling capabilities, it is suitable for a wide range of applications, including tasks from industrial and financial sectors. However, due its high computational complexity, practical reasoning in DatalogMTL is highly challenging. To address this difficulty, we introduce a new reasoning method for DatalogMTL which exploits the magic sets technique—a rewriting approach developed for (non-temporal) Datalog to simulate top-down evaluation with bottom-up reasoning. We have implemented this approach and evaluated it on publicly available benchmarks, showing that the proposed approach significantly and consistently outperformed state-of-the-art reasoning techniques.}, number={14}, journal={Proceedings of the AAAI Conference on Artificial Intelligence}, author={Wang, Shaoyu and Zhao, Kaiyue and Wei, Dongliang and Wałęga, Przemysław Andrzej and Wang, Dingmin and Cai, Hongming and Hu, Pan}, year={2025}, month={Apr.}, pages={15203-15211} }