Reinforcement learning (RL) systems are increasingly being deployed in complex three-dimensional environments. These scenarios often present challenging problems for RL methods due to the increased complexity. Bandit4D, a robust new framework, aims to overcome these limitations by providing a flexible platform for implementing RL agents in 3D scena