Tractable Fragments of Datalog with Metric Temporal Operators

Przemysław A. Wałęga, Bernardo Cuenca Grau, Mark Kaminski, Egor V. Kostylev

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence

Main track. Pages 1919-1925.

https://doi.org/10.24963/ijcai.2020/266

PDF BibTeX Video

Abstract

We study the data complexity of reasoning for several fragments of MTL - an extension of Datalog with metric temporal operators over the rational numbers. Reasoning in the full MTL language is PSPACE-complete, which handicaps its application in practice. To achieve tractability we first study the core fragment, which disallows conjunction in rule bodies, and show that reasoning remains PSPACE-hard. Intractability prompts us to also limit the kinds of temporal operators allowed in rules, and we propose a practical core fragment for which reasoning becomes TC0-complete. Finally, we show that this fragment can be extended by allowing linear conjunctions in rule bodies, where at most one atom can be intensional (IDB); we show that the resulting fragment is NL-complete, and hence no harder than plain linear Datalog.

Keywords

  • Knowledge Representation and Reasoning: Qualitative, Geometric, Spatial, Temporal Reasoning
  • Knowledge Representation and Reasoning: Computational Complexity of Reasoning
  • Knowledge Representation and Reasoning: Logics for Knowledge Representation
Welcome Future Conferences AI Journal Division IJCAI Proceedings Travel Grant Program IJCAI Awards