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 representations which are well refined and bug free. These polished examples are then used to show reasoning mechanisms or the execution of AI search methods. The process of how the knowledge representations themselves 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 acquisition, 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.