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View Code? Open in Web Editor NEWOfficial PyTorch implementation of "Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble" (NeurIPS'21)
License: MIT License
Official PyTorch implementation of "Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble" (NeurIPS'21)
License: MIT License
Hi! Really puzzled by the REM performance as it is a bit counterintuitive that it does not actually work at all but very similar to SAC-N in theory! The appendix doesn't say how the ensemble was implemented and I don't see it in the code. So, I decided to ask if separate nets were used for the ensemble or just different heads with shared first layers as in original REM paper?
Thanks!
Hello, I have a question about the performance of SAC-N or EDAC on AntMaze tasks. Have you ever tested it?
In my experiments based on this official implementation, I found that average returns in evaluation are always 0, which is worse than behavior cloning. Then I try to run with a modified reward (r=4*(r-0.5)) and max Q backup. However, they didn't help.
I'll appreciate it a lot if you give me some related advices. Thanks a lot.
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