Reinforcement learning (RL) models are increasingly being deployed in complex 3D environments. These environments often present unique difficulties for RL methods due to the increased complexity. Bandit4D, a cutting-edge new framework, aims to overcome these limitations by providing a efficient platform for implementing RL agents in 3D worlds. Its