Over the years we have developed the Disciple theory, methodology, and family of tools for building knowledge-based agents. This approach consists in developing an agent shell that can be taught directly by a subject matter expert, in a way that resembles how the expert would teach a human apprentice when solving problems in cooperation. This paper presents the most recent version of the Disciple approach and its implementation in the Disciple-RKF system. Disciple-RKF is based on methods for mixed-initiative problem solving, where the expert solves the more creative problems and the agent solves the more routine ones, integrated teaching and learning, where the agent helps the expert to teach it, by asking relevant questions, and the expert helps the agent to learn, by providing examples, hints and explanations, and multistrategy learning, where the agent integrates multiple learning strategies, such as learning from examples, learning from explanations, and learning by analogy, to learn from the expert how to solves problems.Disciple-RKF has been successfully applied to build learning and reasoning agents for military center of gravity analysis, which are used in several courses at the US Army War College.

Abstract

No abstract

This paper presents an approach to rapid development of virtual planning experts that can collaborate to develop plans of action requiring expertise from multiple domains. The approach is implemented into a new type of software tool, called Disciple-VPT, which includes an extensible library of virtual planning experts from different domains. Teams of such virtual experts can be rapidly assembled from the library to generate complex plans of actions that require their joint expertise. The basic component of the Disciple-VPT tool is the Disciple-VE learning agent shell that can be taught directly by a subject matter expert how to plan, trough planning examples and explanations, in a way that is similar to how the expert would teach an apprentice. Copies of the Disciple-VE shells are used by experts in different domains to rapidly populate the library of virtual experts of Disciple-VPT.