Reinforcement learning (RL) systems are increasingly being deployed in complex spatial environments. These spaces often present challenging difficulties for RL techniques due to the increased dimensionality. Bandit4D, a powerful new framework, aims to address these limitations by providing a flexible platform for developing RL systems in 3D worlds.