Knowledge representation with KnowLang the marXbot case study

Intelligent systems are capable of AI exhibited via knowledge representation and reasoning, which helps to connect abstract knowledge symbols to real-world meanings. This paper presents a formal language for knowledge representation called KnowLang. The language implies a multi-tier specification model emphasizing knowledge corpuses, knowledge base operators and inference primitives. The approach allows for efficient and comprehensive knowledge structuring where ontologies are integrated with rules and Bayesian networks. The paper presents the KnowLang specification constructs formally along with a case study based on a mobile robotics platform.