https://github.com/vdblm/experior
https://github.com/vdblm/experior
Last synced: 10 months ago
JSON representation
- Host: GitHub
- URL: https://github.com/vdblm/experior
- Owner: vdblm
- License: mit
- Created: 2024-04-10T01:10:59.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2024-05-22T18:09:25.000Z (about 2 years ago)
- Last Synced: 2024-05-22T19:29:28.387Z (about 2 years ago)
- Language: Python
- Size: 69.1 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Experts-as-Priors: Sequential Decision Making with Expert Demonstrations under Unobserved Heterogeneity
Installation •
Experiments •
Citation
## Installation
Set up a virtual environment and load it
```bash
python -m venv $ENV_NAME
source $ENV_NAME/bin/activate
```
Install `jax==0.4.14`:
```bash
pip install jax==0.4.14 jaxlib==0.4.14+cuda11.cudnn86 -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html
```
Then, install the `flashbax` package via
```bash
pip install git+https://github.com/instadeepai/flashbax.git
```
Finally, other requirements are installed with `pip install -r requirements.txt`
## Experiments
For bandit experiments, follow the notebook [`notebooks/bandit.ipynb`](./notebooks/bandit.ipynb). For deep sea experiments, run [`notebooks/deep_sea.ipynb`](./notebooks/deep_sea.ipynb).
```