Objectives in ARLBench

ARLBench allows to configure the objectives you’d like to use for your AutoRL methods. These are selected as a list of keywords in the configuration of the AutoRL Environment, e.g. like this:

python arlbench.py autorl.objectives=["reward_mean"]

The following objectives are available at the moment:

  • reward_mean: the mean evaluation reward across a number of evaluation episodes

  • reward_std: the standard deviation of the evaluation rewards across a number of evaluation episodes

  • runtime: the runtime of the training process

  • emissions: the CO2 emissions of the training process, tracked using CodeCarbon.