A Methodology for Modeling and Representing Expert Knowledge that Supports Teaching-Based Intelligent Agent Development (original) (raw)

This paper presents a methodology for modeling and representing expert knowledge that enhances the development of teaching-based intelligent agents. The proposed approach enables domain experts to directly teach agents, minimizing reliance on knowledge engineers. Through the illustration of the Course Of Action (COA) challenge, the methodology aims to accurately capture expert insight for knowledge base construction, facilitating ontology development and effective task reduction, ultimately demonstrating significant performance in knowledge acquisition.