You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Hello! I'm sorry to bother you again. I created a sub optimal policy when running ' mpirun -oversubscribe -np 16 python -u train.py --env-name='FetchPickAndPlace-v1' 2>&1 | tee pick.log'. When the success rate reaches 0.9, it will not increase. Can you analyze the reason? Thank you very much! I'm sorry to bother you again!
The text was updated successfully, but these errors were encountered:
@quyouyuan No worries! In actually, that is the problem of HER itself. The performance of HER on the PickAndPlace task is only around 90%, please refer to Fig.3 in https://arxiv.org/pdf/1802.09464.pdf (this is the OpenAI's report of HER). You may expect to propose some new methods to improve the performance of HER. Furthermore, I also find that it can improve the performance slightly (around 94%) by sampling diverse goals: https://arxiv.org/pdf/2108.07887.pdf.
Hello! I'm sorry to bother you again. I created a sub optimal policy when running ' mpirun -oversubscribe -np 16 python -u train.py --env-name='FetchPickAndPlace-v1' 2>&1 | tee pick.log'. When the success rate reaches 0.9, it will not increase. Can you analyze the reason? Thank you very much! I'm sorry to bother you again!
The text was updated successfully, but these errors were encountered: