Reinforcement learning (RL) agents are increasingly being deployed in complex three-dimensional environments. These environments often present novel obstacles for RL algorithms due to the increased complexity. Bandit4D, a robust new framework, aims to address these limitations by providing a comprehensive platform for implementing RL agents in 3D w