This repository reproduces experiments from the MEEE paper, a model-based reinforcement learning approach that uses ensemble methods to balance exploration and exploitation during training. Built on top of the MBPO framework, it leverages TensorFlow and MuJoCo physics simulation to train RL agents on continuous control tasks like Humanoid. The code provides configuration files and scripts for running experiments with GPU acceleration.