- https://github.com/stanfordnmbl/osim-rl
- https://www.crowdai.org/challenges/nips-2017-learning-to-run
- osim-rl -> submodule containing simulation environment
- rlkit -> submodule containing deep reinforcement learning framework
- notebook_files -> files necessary to run the notebook
- scripts -> scripts used to manage training & simulation
- trained_params -> files composed of trained parameters
- training_statistics -> files composed of training statistics
Installation of the submodules are told inside the submodules.
Run osim-rl-with-farming/sim_farm/farm.py on the opensim-rl conda environment and run scripts/simulate_policy.py with parameter file argument on the rlkit conda environment:
On the first terminal:
source activate opensim-rl
python2 osim-rl-with-farming/sim_farm/farm.py
On the second terminal:
source activate rlkit
python3 scripts/simulate_policy --file <path to parameter file>
Note: To change hyperparameter, see and change method script files.
Run osim-rl-with-farming/farming_scripts/farm.py on the opensim-rl conda environment and run method(ddpg/sac/td3) script on the rlkit conda environment: On the first terminal:
source activate opensim-rl
python2 osim-rl-with-farming/farming_scripts/farm.py
On the second terminal:
source activate rlkit
python3 <path to method(ddpg/sac/td3) script>
- osim-rl-with-farming/farming_scripts -> running multiple environments
- osim-rl-with-farming/sim_farm -> trained parameter simulation
- rlkit-with-farming -> train models using multiple environments
Run following command:
git clone https://github.com/simitii/Learn-to-Move-with-Deep-Reinforcement-Learning.git
Run following command:
git clone --recursive https://github.com/simitii/Learn-to-Move-with-Deep-Reinforcement-Learning.git
- Develop training system - DONE
- Train models(DDPG, SAC, TD3) - DONE
- Get a lot of visual material - DONE
- Write an IPython Notebook about the project - DONE