AdaDQN outperforms strong AutoRL baselines by considering different hyperparameters when the optimization landscape changes 📈 This means that AdaQN changes hyperparameters during training to find a hyperparameter schedule that is adapted to the learning pace of the RL agent 🪡
We recommend using Python 3.11.5. In the folder where the code is, create a Python virtual environment, activate it, update pip and install the package and its dependencies in editable mode:
python3 -m venv env
source env/bin/activate
pip install --upgrade pip setuptools wheel
pip install -e .[dev,gpu]To verify the installation, run the tests as:pytest