A reinforcement learning approach was used, where the agent receives rewards for taking correct actions and penalties for undesirable behaviors. The model was trained to navigate the re:Invent 2018 track from AWS.
To train the model, we defined the settings for its continuous action space. The action space settings influenced the restrictions the agent had when making decisions.
Here is it's action space:
