Using GIPO to support learning in knowledge acquisition and automated planning

Abstract

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