Stratified Negation in Datalog with Metric Temporal Operators


  • David J Tena Cucala University of Oxford
  • Przemysław A Wałęga University of Oxford
  • Bernardo Cuenca Grau University of Oxford
  • Egor Kostylev University of Oslo


Geometric, Spatial, and Temporal Reasoning


We extend DatalogMTL—Datalog with operators from metric temporal logic—by adding stratified negation as failure. The new language provides additional expressive power for representing and reasoning about temporal data and knowledge in a wide range of applications. We consider models over the rational timeline, study their properties, and establish the computational complexity of reasoning. We show that, as in negation-free DatalogMTL, fact entailment in our language is PSPACE-complete in data and EXPSPACE-complete in combined complexity. Thus, the extension with stratified negation does not lead to higher complexity.




How to Cite

Tena Cucala, D. J., Wałęga, P. A., Cuenca Grau, B., & Kostylev, E. (2021). Stratified Negation in Datalog with Metric Temporal Operators. Proceedings of the AAAI Conference on Artificial Intelligence, 35(7), 6488-6495. Retrieved from



AAAI Technical Track on Knowledge Representation and Reasoning