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Implementing Knowledge Representation and Reasoning with Object Oriented Design

arXiv 2601.14840 ↗First posted 21 Jan 2026cs.AI cs.RO cs.SEcited by 0

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Abstract (arXiv)

This paper introduces KRROOD, a framework designed to bridge the integration gap between modern software engineering and Knowledge Representation & Reasoning (KR&R) systems. While Object-Oriented Programming (OOP) is the standard for developing complex applications, existing KR&R frameworks often rely on external ontologies and specialized languages that are difficult to integrate with imperative code. KRROOD addresses this by treating knowledge as a first-class programming abstraction using native class structures, bridging the gap between the logic programming and OOP paradigms. We evaluate the system on the OWL2Bench benchmark and a human-robot task learning scenario. Experimental results show that KRROOD achieves strong performance while supporting the expressive reasoning required for real-world autonomous systems.

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References · 7

  1. 2023DeepOnto: A Python Package for Ontology Engineering with Deep Learningcited by 20
  2. 2023Knowledge-Driven Robot Program Synthesis from Human VR Demonstrationscited by 2
  3. 2023OWL Reasoners still useable in 2023cited by 2
  4. 2025OWLAPY: A Pythonic Framework for OWL Ontology Engineeringcited by 2
  5. 2024OWLOOP: Interfaces for Mapping OWL Axioms into OOP Hierarchiescited by 1
  6. 2024owl2proto: Enabling Semantic Processing in Modern Cloud Micro-Servicescited by 1
  7. 2025KERAIA: An Adaptive and Explainable Framework for Dynamic Knowledge Representation and Reasoningcited by 1

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