Using GIPO to support learning in knowledge acquisition and automated planning

The process of how knowledge is acquired and formulated in knowledge-intensive AI is difficult for a student to grasp without practical experience. Often, AI text books and lecture notes contain examples of logic formula or structured knowledge represen-tations which are well refined and bug free. These polished examples are then used to show reasoning mechanisms or the execu-tion of AI search methods. The process of how the knowledge representations them-selves are acquired and validated is often neglected. In this paper we describe the use of a tool called GIPO for teaching AI students. GIPO helps students understand and integrate aspects of knowledge acqui-sition, knowledge engineering, automated planning and machine learning. We show how the tool’s features supports teaching and the student’s learning experience, and helps integrate the theory and practice in a range of AI and related subject areas. 1