Reinforcement learning (RL) agents are increasingly being deployed in complex spatial environments. These environments often present challenging problems for RL techniques due to the increased degrees of freedom. Bandit4D, a cutting-edge new framework, aims to address these hurdles by providing a flexible platform for training RL solutions in 3D si