Implementation of the Deep Deterministic Policy Gradient and Hindsight Experience Replay.
Last updated Jul 22, 2026
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README
DDPG + HER
Implementation of the Deep Deterministic Policy Gradient with Hindsight Experience Replay Extension on the MuJoCo's 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
- opencvcontribpython == 3.4.0.12
- psutil == 5.4.2
- torch == 1.4.0
Installation
pip3 install -r requirements.txtUsage
mpirun -np $(nproc) python3 -u main.pyDemo
Result
Reference
- Continuous control with deep reinforcement learning_, Lillicrap et al., 2015
- Hindsight Experience Replay_, Andrychowicz et al., 2017
- Multi-Goal Reinforcement Learning: Challenging Robotics Environments and Request for Research_, Plappert et al., 2018
