Reinforcement learning (RL) agents are increasingly being deployed in complex 3D environments. These environments often present unique difficulties for RL techniques due to the increased complexity. Bandit4D, a robust new framework, aims to overcome these hurdles by providing a efficient platform for implementing RL systems in 3D simulations. Its s