Hybrid Methods of Knowledge Elicitation within a Unified Representational Knowledge Scheme

This paper presents a case study showing how hybrid methods of knowledge elicitation can be used to build models in support of the functioning of intelligent agents. What facilitates both the elicitation of knowledge and its conversion into actionable models is the use of a unified representational knowledge scheme – specifically, an unambiguous, ontologically grounded metalanguage that serves as the language of all recorded knowledge as well as the language in which agents remember and reason.

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