AI Grid and our members in the press:
Reinforcement learning: robots learn better with rewards
Julian Eßer is a member of AI Grid and researches intelligent transportation robots for the factories of the future at the Fraunhofer Institute. Here he explains how robots learn to make decisions in order to receive as many rewards as possible, i.e. to be as successful as possible.