Reinforcement learning (RL) models are increasingly being deployed in complex three-dimensional environments. These spaces often present novel problems for RL methods due to the increased complexity. Bandit4D, a cutting-edge new framework, aims to overcome these hurdles by providing a efficient platform for training RL agents in 3D scenarios. Its m