Open DeepAnonymous opened 1 year ago
Also, could you please give a short comment about feedback_type
, I am confused with 0,1,2 options.
For me, only feedback_type = 0
makes sense, because it takes ensemble-wise index std_Q_critic_list[en_index]
, instead of std_Q_critic_list[0]
as feedback_type = 1
In RL, I don't think we should pay too much attention in loss of critic actor or anything else. The key indicator is the reward sum. For the deedback_type, I think that is from the ablation study.
Hi,
I tried to log policy and critic losses as well as reward using Tensorboard. I run training using default setting with sz50.
I noticed that critic losses keep increasing. Does this even make sense?
I wonder is there any issue with the code regarding critic losses, could you please have a check/comment on this.
Thank you.