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

This paper introduces a general domain modeling methodology for building knowledge-based agents that is tightly integrated with an apprenticeship multistrategy learning approach to knowledge acquisition and problem solving. This methodology allows domain experts to naturally express their expertise in a form that supports several aspects of knowledge base development, including ontology formation, rule learning, and natural language generation of solutions and justifications.