Goal-Driven Reasoning in DatalogMTL with Magic Sets

• URL: http://arxiv.org/abs/2412.07259v2
• Date: Mon, 23 Dec 2024 02:24:15 GMT
• Title: Goal-Driven Reasoning in DatalogMTL with Magic Sets
• Authors: Shaoyu Wang, Kaiyue Zhao, Dongliang Wei, Przemysław Andrzej Wałęga, Dingmin Wang, Hongming Cai, Pan Hu,
• Abstract summary: DatalogMTL is a powerful rule-based language for temporal reasoning. We introduce a new reasoning method for DatalogMTL which exploits the magic sets technique. We implement this approach and evaluate it on several publicly available benchmarks.
• Score: 4.885086628404422
• License:
• 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 implement this approach and evaluate it on several publicly available benchmarks, showing that the proposed approach significantly and consistently outperforms performance of the state-of-the-art reasoning techniques.

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