Implementing Knowledge Representation and Reasoning with Object Oriented Design
It addresses a problem for developers of complex applications by enabling better integration between KR&R and modern software engineering, though it appears incremental as it builds on existing paradigms.
This paper tackles the integration gap between Knowledge Representation & Reasoning (KR&R) systems and Object-Oriented Programming (OOP) by introducing KRROOD, a framework that treats knowledge as a first-class programming abstraction using native class structures, achieving strong performance on benchmarks like OWL2Bench and a human-robot task learning scenario.
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.