Today, hardly any area of life can be imagined without AI. Well-known method fields in AI are unsupervised and supervised learning, which predominantly deal with static problems. Reinforcement learning (RL), on the other hand, is an area of Machine Learning, which deals with learning optimal behavior in dynamic environments. Reinforcement learning is found in a growing number of applications. These include autonomous vehicles and drones, intelligent home control or control of production plants and logistics fleets. Likewise, the behavior of robots or prostheses can be learned with RL. But also AI stock market agents or recommendation systems for movies and music are based on RL. In addition, there are virtual assistants, e.g. for e-mails and appointments. Also the adaptation of large language models like ChatGPT is done with RL with human feedback.