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