Skip to content

Code accompanying paper "Plan To Predict: Learning an Uncertainty-Foreseeing Model for Model-Based Reinforcement Learning".

Notifications You must be signed in to change notification settings

ZifanWu/Plan-to-Predict

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

17 Commits
 
 
 
 

Repository files navigation

Plan-To-Predict

This code accompanies the paper "Plan To Predict: Learning an Uncertainty-Foreseeing Model for Model-Based Reinforcement Learning".

Installation

  1. Install MuJoCo 1.50 at ~/.mujoco/mjpro150 and copy your license key to ~/.mujoco/mjkey.txt
  2. Clone P2P
git clone https://github.com/ZifanWu/Plan-to-Predict.git
  1. Create a conda environment and install Plan-to-Predict
cd src/Plan-to-Predict
conda env create -f environment/gpu-env.yml
conda activate p2p
pip install -e .

Usage

python src/main_p2p.py --num_epoch 150

Optimal parameters

The optimal parameters are contained in .src/configs/ folder.

Reference

@article{wu2022plan,
  title={Plan To Predict: Learning an Uncertainty-Foreseeing Model For Model-Based Reinforcement Learning},
  author={Wu, Zifan and Yu, Chao and Chen, Chen and Hao, Jianye and Zhuo, Hankz Hankui},
  journal={Advances in Neural Information Processing Systems},
  volume={35},
  pages={15849--15861},
  year={2022}
}

About

Code accompanying paper "Plan To Predict: Learning an Uncertainty-Foreseeing Model for Model-Based Reinforcement Learning".

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages