DDPG + HER

Implementation of the deep deterministic policy gradient with hindsight experience replay extension on mujoco robotic FetchPickAndPlace environment.

Visit vanilla_DDPG branch for the implementation without the HER extention.

Dependencies

• gym == 0.17.2
• matplotlib == 3.1.2
• mpi4py == 3.0.3
• mujoco-py == 2.0.2.13
• numpy == 1.19.1
• opencv_contrib_python == 3.4.0.12
• psutil == 5.4.2
• torch == 1.4.0

Installation

pip3 install -r requirements.txt

Usage

mpirun -np $(nproc) python3 -u main.py

Demo

Result

Reference

1. Continuous control with deep reinforcement learning, Lillicrap et al., 2015
2. Hindsight Experience Replay, Andrychowicz et al., 2017
3. Multi-Goal Reinforcement Learning: Challenging Robotics Environments and Request for Research, Plappert et al., 2018

Acknowledgement

All the credit goes to @TianhongDai for his simplified implementation of the original OpenAI's code.

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