Pushing the Boundaries of Tractable Multiperspective Reasoning: A Deduction Calculus for Standpoint EL+

Lucía Gómez ÁlvarezLucía Gómez Álvarez, Sebastian RudolphSebastian Rudolph, Hannes StraßHannes Straß

ISBN: 978-1-956792-02-7
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Lucía Gómez Álvarez, Sebastian Rudolph, Hannes Straß
Pushing the Boundaries of Tractable Multiperspective Reasoning: A Deduction Calculus for Standpoint EL+
In Pierre Marquis, Tran Cao Son, Gabriele Kern-Isberner, eds., Proceedings of the 20th International Conference on Principles of Knowledge Representation and Reasoning, 333-343, 2023. IJCAI Inc

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KurzfassungAbstract
Standpoint EL is a multi-modal extension of the popular description logic EL that allows for the integrated representation of domain knowledge relative to diverse standpoints or perspectives. Advantageously, its satisfiability problem has recently been shown to be in PTime, making it a promising framework for large-scale knowledge integration. In this paper, we show that we can further push the expressivity of this formalism, arriving at an extended logic, called Standpoint EL+, which allows for axiom negation, role chain axioms, self-loops, and other features, while maintaining tractability. This is achieved by designing a satisfiability-checking deduction calculus, which at the same time addresses the need for practical algorithms. We demonstrate the feasibility of our calculus by presenting a prototypical Datalog implementation of its deduction rules.
Projekt:Project: ScaDS.AI
Forschungsgruppe:Research Group: Computational LogicComputational Logic

@inproceedings{{RS2023,
  author    = {Luc{\'{\i}}a G{\'{o}}mez {\'{A}}lvarez and Sebastian Rudolph and
               Hannes Stra{\ss}},
  title     = {Pushing the Boundaries of Tractable Multiperspective Reasoning: A
               Deduction Calculus for Standpoint {EL+}},
  editor    = {Pierre Marquis and Tran Cao Son and Gabriele Kern-Isberner},
  booktitle = {Proceedings of the 20th International Conference on Principles of
               Knowledge Representation and Reasoning},
  publisher = {IJCAI Inc},
  year      = {2023},
  pages     = {333-343},
  doi       = {10.24963/kr.2023/33}
}