Reinforcement Learning in Industrial Applications
Although reinforcement learning has gained great success in computer games, there are only few yet known implementations in ndustrial applications. This despite the fact that reinforcement learning offers interesting methods to optimise the control of nonlinear processes. In this thesis we have used two model free reinforcement learning algorithms (PPO and DDPG) to control three different simulati