Comments (4)
Also, which version of D4RL were you using (also in COMBO)?
The reason why I ask is that the buffer quality is quite different in v0~v2. (you could refer to the TD3BC paper for details).
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Hi, I really appreciate your open source code. My question is how is your performance number reported in the paper.
For example, in Table 1, do you use the max evaluation return during the learning process or use the last evaluation return. The return of the policy has large variance in different iteration.
Thanks,
Yue
I have the same problem, When i run the demo not in mixed, the results has large variance.
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@HYDesmondLiu The config file in this repo says they used '-v0' dataset for MOPO. But I'm still curious about the dataset version used in COMBO, is COMBO's source code even released?
I am also having trouble stabilizing MOPO's performance. The variance of performance across epochs is quite huge.
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@typoverflow
AFAIK, COMBO source code is not shared. As I recall they use D4RL v2 buffers since the performance between v0 and v2 is quite different. You could easily spot the difference.
"Some" DRL methods are notorious for being unreproducible.
You could refer to this paper and other related research for more information.
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Related Issues (13)
- installing viskit HOT 1
- MOPO predict
- What is the difference between MOPO and SAC
- Any plan to fit in tensorflow_gpu 2 or 2.7?
- ModuleNotFoundError: No module named 'ray.autoscaler.commands'
- running example gives: "ModuleNotFoundError: No module named 'mopo.env'" HOT 4
- In the current code, spectral normalization does not seem to be properly applied HOT 1
- Why MOPO is given access to terminal function in rollout generation? HOT 2
- What's the difference between MOPO-no_penalty and MBPO
- No module named 'examples.instruments' HOT 1
- The working packages of viskit have been updated in July 2021
- Open the hiv dataset
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