Reinforcement learning (RL) systems are increasingly being deployed in complex three-dimensional environments. These environments often present challenging problems for RL techniques due to the increased complexity. Bandit4D, a powerful new framework, aims to mitigate these limitations by providing a efficient platform for developing RL agents in 3