Reinforcement learning (RL) agents are increasingly being deployed in complex 3D environments. These spaces often present novel difficulties for RL techniques due to the increased degrees of freedom. Bandit4D, a robust new framework, aims to overcome these hurdles by providing a flexible platform for training RL systems in 3D worlds. Its scalable w