PrimAITE supports the ability to use different variations on a scenario at different episodes. This can be used to increase domain randomisation to prevent overfitting, or to set up curriculum learning to train agents to perform more complicated tasks.
When using a fixed scenario, a single yaml config file is used. However, to use episode schedules, PrimAITE uses a directory with several config files that work together.
Defining variations in the config file.
Base scenario
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The base scenario is essentially the same as a fixed YAML configuration, but it can contain placeholders that are populated with episode-specific data at runtime. The base scenario contains any network, agent, or settings that remain fixed for the entire training/evaluation session.
Users must define which combination of scenario variations should be loaded in each episode. This takes the form of a YAML file with a relative path to the base scenario and a list of paths to be loaded in during each episode.
It takes the following format:
..code-block:: yaml
base_scenario: base.yaml
schedule:
0: # list of variations to load in at episode 0 (before the first call to env.reset() happens)
- laydown_1.yaml
- attack_1.yaml
1: # list of variations to load in at episode 1 (after the first env.reset() call)
For more information please refer to the ``Using Episode Schedules`` notebook in either :ref:`Executed Notebooks` or run the notebook interactively in ``notebooks/example_notebooks/``.
