System requirements:
- Python3.6
- python3-venv
- tkinter (python3-tk)
All required python packages can be found in requirements.txt. Install using
python3 -m venv env
source env/bin/activate
pip3 install -r requirements.txt
NOTE: This requires tkinter, which can be installed on ubuntu by apt-get install python3-tk.
This package contains the implementation of the Natural Actor-Critic (NAC) algorithm.
You can find the actual implementation in nac.py, and available models in model.py.
This section contains usage descriptions and code examples.
You can also find complete example usages of the interface in bayesian_opt.py, and run_experiment.py.
For training use nac.nac.train(...). Hyperparameters are directly passed to this function, and are explained in the docstring of that function. We do not repeat this documentation here to avoid inconsistency.
Random values are generated by pytorch and numpy. To set a seed for these libraries, use
torch.manual_seed(seed)
np.random.seed(seed)
You can use run_model.py to load and run a saved model .pt file.
- Natural Actor-Critic https://homes.cs.washington.edu/~todorov/courses/amath579/reading/NaturalActorCritic.pdf
- Setting up experiments http://www-clmc.usc.edu/publications/p/peters-ICHR2003.pdf
- Pytorch Documentation https://pytorch.org/docs/stable/index.html
- Numpy Documentation https://docs.scipy.org/doc/numpy/reference/