Reinforcement learning (RL) models are increasingly being deployed in complex spatial environments. These scenarios often present challenging difficulties for RL algorithms due to the increased degrees of freedom. Bandit4D, a powerful new framework, aims to address these limitations by providing a efficient platform for developing RL systems in 3D