Reinforcement Learning in a Noisy Environment: Light-seeking Robot

Despite many promising results from the use of reinforcement learning in simulated robot worlds, its use in real robot worlds is relatively rare. This paper addresses challenges related to real robot worlds and shows how reinforcement learning combined with linear function approximation can solve many of them. Experiments are performed using a light-seeking robot built with the Lego Mindstorms Robotics Invention System. Key-Words: reinforcement learning, exploration strategies, light-seeking robot, linear approximation, gradient descent