Learning to Play the BRIO Labyrinth Game

In this article, we present the BRIO labyrinth system, a challenging real-world, robotic system suited as testbed for an empirical analysis and comparison of Reinforcement Learning (RL) algorithms. We discuss the development of both the testbed itself as well as a realistic simulation of the system and first experiments with RL algorithms on the simulated BRIO system. Furthermore, we briefly sketch some experiments that will be conducted with human probands on the BRIO system that will yield some insights into sensorimotor learning of humans.