Open zyw19970608 opened 4 days ago
Hello! The data augmentation technique is borrowed from SURF (Park et al., 2022). Empirically, I found that this technique doesn't significantly impact performance in our meta world environments. Therefore, in this code I have chosen not to use data augmentation for meta world.
Thank you for your attention!
I'm interested in understanding the rationale behind not incorporating data augmentation techniques in the meta world environments. Specifically, I noticed that in the function self.reward_model.train_reward(), there isn't a parameter for data augmentation like data_aug_ratio, which is used in self.reward_model.train_reward_iter(num_iters).
Does this imply that methods without data augmentation perform better in meta world environments, or is there another reason for this design choice?
Thank you for your insights!