David Heik is a research associate and PhD candidate at HTW Dresden. His research focuses on the application of dmulti-agent reinforcement learning to dynamic scheduling problems in industrial production systems. In his doctoral work, he investigates how learning-based, self-organizing decision mechanisms can improve efficiency, robustness, and adaptability in complex manufacturing environments.