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