Implementation of DQN model to improve stability proceedures in the Chord protocol

How to Run

• Create a python vertual environment with conda or pip
• Check your CUDA version on your system:

nvidia-smi

• Ensure that you have pytorch install from the pytorch Official Website, copy the command according to CUDA version for example:

conda install pytorch torchvision torchaudio pytorch-cuda=12.4 -c pytorch -c nvidia

or

pip install pytorch torchvision torchaudio pytorch-cuda=12.4 -c pytorch -c nvidia

• After pytorch is installed, you must install all of the other dependencies via the requirments.txt file

pip install -r /path/to/requirements.txt

or create your conda environment via the requirements.txt

conda create --name <env> --file requirements.txt

Additionally you may need to run the following command in order to run the custom environment:

pip install -e .

run via this command

py run_gymnasium_env.py

Quick Info

• Currently there is a trained model Chord_model.pt that you can test. Other than that you can run the training and tweak what ever you would like.