Using the ARLBench States¶
In addition to providing different objectives, ARLBench also provides insights into the target algorithms’ internal states. This is done using so called StateFeatures.
As of now, we implement the GradInfo state feature which returns the norm and variance of the gradients observed during training. The used state features can be defined using the state_features key in the config passed to the AutoRL Environment. Please include grad_info in this list if you want to use this state feature for your approach. We are currently working on extending this part of ARLBench to other state features as well.