Policy Gradients, DDPG, and TD3 in 2 DOF arm gym env
An episode of the 2 link arm environment.
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.
Download the folder modified-gym-env from pybullet-gym-env
-
Python 3.6.10
-
PyTorch >= 1.7.0
-
gym 0.17.3
-
numpy >= 1.16.2
-
matplotlib >= 3.1.1
.
├── src # Python scripts
│ ├── policy_gradients.py # Policy Gradients algorithm
│ ├── DDPG.py # Deep Deterministic Policy Gradients algorithm
│ └── TD3.py # Twin Delayed DDPG algorithm
├── demo.gif # Results
└── README.md
There are 3 methods you can try, namely policy gradients, ddpg, and td3, with corresponding file name.
ex. if you want to try policy gradients, just do
python policy_gradients.py
- Arthur Hsieh - Initial work - arthur960304