Implementing Knowledge Representation and Reasoning with Object Oriented Design
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arXiv
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| Auteurs principaux: | , , , , , , |
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| Format: | Preprint |
| Publié: |
2026
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| _version_ | 1866908779611684864 |
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| author | Bassiouny, Abdelrhman Schierenbeck, Tom Arion, Sorin Alt, Benjamin Vasantakumaar, Naren Nguyen, Giang Beetz, Michael |
| author_facet | Bassiouny, Abdelrhman Schierenbeck, Tom Arion, Sorin Alt, Benjamin Vasantakumaar, Naren Nguyen, Giang Beetz, Michael |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_14840 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Implementing Knowledge Representation and Reasoning with Object Oriented Design Bassiouny, Abdelrhman Schierenbeck, Tom Arion, Sorin Alt, Benjamin Vasantakumaar, Naren Nguyen, Giang Beetz, Michael Artificial Intelligence Robotics Software Engineering 68T30 I.2.4; I.2.9; I.2.5 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. |
| title | Implementing Knowledge Representation and Reasoning with Object Oriented Design |
| topic | Artificial Intelligence Robotics Software Engineering 68T30 I.2.4; I.2.9; I.2.5 |
| url | https://arxiv.org/abs/2601.14840 |