Reinforcement learning (RL) systems are increasingly being deployed in complex three-dimensional environments. These spaces often present novel difficulties for RL techniques due to the increased degrees of freedom. Bandit4D, a powerful new framework, aims to overcome these limitations by providing a comprehensive platform for implementing RL agent