Reasoner = Logical Calculus + Rule Engine

David CarralDavid Carral, Irina DragosteIrina Dragoste, Markus KrötzschMarkus Krötzsch

ISBN: 1610-1987
DOI Link

David Carral, Irina Dragoste, Markus Krötzsch
Reasoner = Logical Calculus + Rule Engine
KI, 2020

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KurzfassungAbstract
We propose using rule languages to encode complex reasoning algorithms in a declarative way. This approach -- which follows the classical slogan "Algorithm = Logic + Control" -- promises to turn high-level specifications of logical calculi as systems of inference rules into declarative rule-based models that can be executed on state-of-the-art rule engines.
More precisely, given some input reasoning algorithm for some logic, we show how to produce a rule-based calculus; that is, a fixed rule set that can be used to replicate the consequences of the input algorithm. Simple rule languages suffice for simple logics, and we review our results on using Datalog rules to reason in the description logic EL. For more expressive logics, a suitably expressive yet implementable rule language often seems to be missing. To fill this gap, we consider an extension of Datalog with sets, Datalog(S), that can be executed by modern existential-rule reasoners, and we use it to present a rule-based reasoning calculus for the expressive description logic ALC.
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Weitere Informationen unter:Further Information: Link
Projekt:Project: CPEC
Forschungsgruppe:Research Group: Wissensbasierte SystemeKnowledge-Based Systems

The final publication is available at Springer via http://dx.doi.org/10.1007/s13218-020-00667-6.

@article{CDK2020,
  author    = {David Carral and Irina Dragoste and Markus Kr{\"{o}}tzsch},
  title     = {Reasoner = Logical Calculus + Rule Engine},
  journal   = {KI},
  publisher = {Springer},
  year      = {2020},
  doi       = {10.1007/s13218-020-00667-6}
}