Conditional Syntax Splitting for Non-monotonic Inference Operators


  • Jesse Heyninck Open Universiteit, the Netherlands
  • Gabriele Kern-Isberner TU Dortmund University, Germany
  • Thomas Meyer University of Cape Town, South-Africa Centre for Artificial Intelligence Research (CAIR), South-Africa
  • Jonas Philipp Haldimann FernUniversität in Hagen, Germany
  • Christoph Beierle FernUniversität in Hagen, Germany



KRR: Nonmonotonic Reasoning


Syntax splitting is a property of inductive inference operators that ensures we can restrict our attention to parts of the conditional belief base that share atoms with a given query. To apply syntax splitting, a conditional belief base needs to consist of syntactically disjoint conditionals. This requirement is often too strong in practice, as conditionals might share atoms. In this paper we introduce the concept of conditional syntax splitting, inspired by the notion of conditional independence as known from probability theory. We show that lexicographic inference and system W satisfy conditional syntax splitting, and connect conditional syntax splitting to several known properties from the literature on non-monotonic reasoning, including the drowning effect.




How to Cite

Heyninck, J., Kern-Isberner, G., Meyer, T., Haldimann, J. P., & Beierle, C. (2023). Conditional Syntax Splitting for Non-monotonic Inference Operators. Proceedings of the AAAI Conference on Artificial Intelligence, 37(5), 6416-6424.



AAAI Technical Track on Knowledge Representation and Reasoning