🔥 Getting Started

In the /experiments folder, example runs can be found for different Gymnasium environments.

For example, you can run the cartpole example using DQN with the following command:

pants run //experiments/gym/train_dqn_cartpole.py@resolve=base

This comes with a lot of predefined arguments, such as the learning rate, the amount of hidden layers, the batch size, etc. You can find all the arguments in the experiments/gym/train_dqn_cartpole.py file.

📊 Tensorboard

To visualize the training process, you can use Tensorboard. To do so, run the following command:

pants run //:tensorboard -- --logdir ./mllogs

This will start a Tensorboard server on localhost:6006. You can now open your browser and go to http://localhost:6006 to see the training process where you can see the rewards over time, the loss over time, etc.