Reinforcement learning (RL) systems are increasingly being deployed in complex spatial environments. These spaces often present unique problems for RL algorithms due to the increased dimensionality. Bandit4D, a robust new framework, aims to address these challenges by providing a comprehensive platform for developing RL solutions in 3D simulations.