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The implementation seems to be different from the method in the paper #70

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zmccmzty opened this issue Jan 17, 2024 · 1 comment

zmccmzty commented Jan 17, 2024 •

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It looks like the policy and the discriminator are trained together at the same rate with single optimizer and combined loss (https://github.com/nv-tlabs/ASE/blob/21257078f0c6bf75ee4f02626260d7cf2c48fee0/ase/learning/ase_agent.py#L280C1-L280C1). It seems to be different from the pseudocode in the paper, where they were trained separately. Any idea about what's the reason for this? Or am I missing something?

Winston-Gu commented Jan 22, 2024

I have the same question here ...

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