Complexity of Approximate Query Answering under Inconsistency in Datalog+/-

Authors: Thomas Lukasiewicz, Enrico Malizia, Cristian Molinaro

IJCAI 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical In this paper, we analyze the complexity of conjunctive query answering under these two semantics for a wide range of Datalog languages. We give a precise picture of the complexity of BCQ answering from existential rules under the IAR, ICR, GIAR, and GICR semantics, which is summarized in Fig. 1; it ranges from membership in AC0 to 2EXP-completeness.
Researcher Affiliation Academia 1 Department of Computer Science, University of Oxford, UK 2 Department of Computer Science, University of Exeter, UK 3 DIMES, University of Calabria, Italy
Pseudocode No The paper contains theoretical discussions, theorems, and proofs, but no structured pseudocode or algorithm blocks.
Open Source Code No The paper does not provide any explicit statements about releasing source code or links to a code repository for the described methodology.
Open Datasets No This is a theoretical paper that focuses on complexity analysis of query answering under inconsistency in Datalog. It does not utilize or refer to publicly available datasets in the context of empirical evaluation.
Dataset Splits No As a theoretical paper, it does not involve empirical experiments with datasets that would require training, validation, or test splits.
Hardware Specification No As a theoretical paper, no specific hardware used for experiments is mentioned or described.
Software Dependencies No The paper is theoretical and focuses on complexity analysis rather than empirical implementation. Therefore, it does not list software dependencies with version numbers.
Experiment Setup No This is a theoretical paper that does not involve empirical experiments, and thus no experimental setup details or hyperparameters are provided.