@conference{224,
  keywords = {Datalog, Non-monotonic reasoning, Preferential Reasoning, Defeasible Implication, Knowledge Representation, Rational closure},
  author = {Michael Harrison and Tommie Meyer},
  title = {Rational preferential reasoning for datalog},
  abstract = {Datalog is a powerful language that can be used to represent explicit knowledge and compute inferences in knowledge bases. Datalog cannot represent or reason about contradictory rules, though. This is a limitation as contradictions are often present in domains that contain exceptions. In this paper, we extend datalog to represent contradictory and defeasible information. We define an approach to efficiently reason
about contradictory information in datalog and show that it satisfies the KLM requirements for a rational consequence relation. Finally, we introduce an implementation of this approach in the form of a defeasible datalog reasoning tool and evaluate the performance of this tool.},
  year = {2019},
  journal = {Forum for Artificial Intelligence Research},
  chapter = {232-243},
  month = {03/12-06/12},
  publisher = {CEUR},
  isbn = {1613-0073},
  url = {http://ceur-ws.org/Vol-2540/FAIR2019_paper_67.pdf},
}