Reinforcement learning (RL) agents are increasingly being deployed in complex three-dimensional environments. These spaces often present unique problems for RL algorithms due to the increased dimensionality. Bandit4D, a robust new framework, aims to overcome these limitations by providing a flexible platform for training here RL solutions in 3D sce