YaoYao1995/MEEE
PyTorch/TensorFlow implementation of a model-based reinforcement learning algorithm for efficient exploration and exploitation.
Not currently ranked — collecting fresh signals.
star history
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.
Frequently asked
- What is YaoYao1995/MEEE?
- PyTorch/TensorFlow implementation of a model-based reinforcement learning algorithm for efficient exploration and exploitation.
- Is MEEE open source?
- Yes — YaoYao1995/MEEE is open source, released under the MIT license.
- What language is MEEE written in?
- YaoYao1995/MEEE is primarily written in Python.
- How popular is MEEE?
- YaoYao1995/MEEE has 434 stars on GitHub.
- Where can I find MEEE?
- YaoYao1995/MEEE is on GitHub at https://github.com/YaoYao1995/MEEE.