Teaching Distributed Artificial Intelligence with RoboRally

Teaching Artificial Intelligence (AI) or multi-agent systems is a challenging task as algorithms are in question which are advantageous in highly complex and dynamic environments. Explaining multi-agent systems (MAS) in lectures requires interactive approaches accompanied by exercises. The key challenge in using practical exercises within lectures on MAS is to establish an environment for testing which is extremely time consuming. It is not reasonable that students do this work as they do have not enough time focussing on the important aspects. In this paper, we introduce a system which supports experimenting with AI and Distributed Artificial Intelligence (DAI) algorithms concurrently to the lecture. Our system is based on a board game called RoboRally. Different issues from the field of AI and DAI can be implemented and tested in a kind of challenge.