Stratified negation in limit datalog programs

Conference item

There has recently been an increasing interest in declarative data analysis, where analytic tasks are specified using a logical language, and their implementation and optimisation are delegated to a general-purpose query engine. Existing declarative languages for data analysis can be formalised as variants of logic programming equipped with arithmetic function symbols and/or aggregation, and are typically undecidable. In prior work, the language of limit programs was proposed, which is sufficiently powerful to capture many analysis tasks and has decidable entailment problem. Rules in this language, however, do not allow for negation. In this paper, we study an extension of limit programs with stratified negation-as-failure. We show that the additional expressive power makes reasoning computationally more demanding, and provide tight data complexity bounds. We also identify a fragment with tractable data complexity and sufficient expressivity to capture many relevant tasks.

Authors: Kaminski, M; Cuenca Grau, B; Kostylev, E; Motik, B; Horrocks, I

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: IJCAI-ECAI 2018
• Host title: 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence, July 13-19, 2018
• Journal: IJCAI 2018
• Pages: 1875-1881
• Publication date: 2018-07-19
• Acceptance date: 2018-04-16
• DOI: 10.24963/ijcai.2018/259
• ISBN: 9780999241127