Reinforcement learning (RL) agents are increasingly being deployed in complex spatial environments. These environments often present challenging obstacles for RL algorithms due to the increased complexity. Bandit4D, a cutting-edge new framework, aims to overcome these challenges by providing a comprehensive platform for training RL solutions in 3D