Abstract not found

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. Key Words: multistrategy apprenticeship learning, problem solving through task reduction, mixed-initiative reasoning, plausible version spaces, rule learning, ontology, agent development, military center of gravity analysis 2 1.

. This chapter describes the application of seven approaches to support three basic task types of design (design selection, parametric design and design synthesis). The specialization of these approaches to practical design techniques is analyzed and illustrated with examples. 1 Introduction The engineering design process critically influences factors of lead time and cost in product development; factors that frequently determine the profitability of products in competitive markets. To reduce the lead time and cost of product development, it is important to first characterize the design process so that new technologies and methodologies can be developed to improve its efficiency. Characterization of the design process requires both a natural process view of design and an artificial process view of design (Kannapan and Marshek, 1992a). The natural process view emphasizes cognitive and social processes such as identification of customer needs, and team design with multiple perspectives. ...