[ICC'21 - DRL-SFCP] Implementation of our paper "DRL-SFCP: Adaptive Service Function Chains Placement with Deep Reinforcement Learning", accepted by ICC 2021.
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There seems to be some problems in the solver A3CGcnSeq2SeqSolver. #11
First of all, thank you very much for sharing, I learned a lot from your code.
But during my analysis, I noticed some problems in the method "solve" of A3CGcnSeq2SeqSolver class.
In the while loop at line 70 of solver/learning/a3c_gcn_seq2seq/sover.py,
the sub_obs = encoder_obs causes the observations of the subenvironment to be repeatedly refreshed by the old state.
So sub_obs = next_sub_obs at line 90 will have no effect.
The value of next_sub_obs is not used.
It should be correct to write sub_obs = encoder_obs outside the loop to do only the first initialization.
Is my analysis correct? I see Virne also has this problem in your new project, so it's probably not a debugging error.
Thanks again for sharing the code, that's all I was wondering.
First of all, thank you very much for sharing, I learned a lot from your code. But during my analysis, I noticed some problems in the method "solve" of A3CGcnSeq2SeqSolver class.
In the while loop at line 70 of solver/learning/a3c_gcn_seq2seq/sover.py, the
sub_obs = encoder_obscauses the observations of the subenvironment to be repeatedly refreshed by the old state. Sosub_obs = next_sub_obsat line 90 will have no effect. The value ofnext_sub_obsis not used.It should be correct to write
sub_obs = encoder_obsoutside the loop to do only the first initialization.Is my analysis correct? I see Virne also has this problem in your new project, so it's probably not a debugging error.
Thanks again for sharing the code, that's all I was wondering.