Reinforcement learning (RL) agents are increasingly being deployed in complex three-dimensional environments. These spaces often present unique problems for RL methods due to the increased dimensionality. Bandit4D, a cutting-edge new framework, aims to overcome these challenges by providing a comprehensive platform for implementing RL systems in 3D