End colloquium Kahao Cheung

Reinforcement Learning for 3D Concrete Printing

In the dynamic environment of 3D concrete printing, where both material variations and the printing environment can significantly affect product quality, Reinforcement Learning can serve as a tool to learn to adapt the system to different variations during printing. To bring 3D concrete printing closer to consistent product and process quality, this thesis addresses the research gap between reinforcement learning and 3DCP through the development of a modular framework focusing on quality control performance within a 3DCP environment.