Reinforcement learning (RL) systems are increasingly being deployed in complex spatial environments. These environments often present challenging difficulties for RL techniques due to the increased complexity. Bandit4D, a cutting-edge new framework, aims to mitigate these hurdles by providing a comprehensive platform for developing RL agents in 3D