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Hello,
In the asynchronous dqn paper, they also described an on policy method, the advantage actor-critic (A3C), which achieved better results than others, do you currently have any plan to include this method in this repo as well?
Because I am working off this repo as a starting point, and attempt to reproduce the results of the A3C method on the continuous action domain, but I am still trying to figure out the network model they used in the physical state case when apply to Mojoco, and how the policy gradient is accumulated.
The text was updated successfully, but these errors were encountered:
Hello,
In the asynchronous dqn paper, they also described an on policy method, the advantage actor-critic (A3C), which achieved better results than others, do you currently have any plan to include this method in this repo as well?
Because I am working off this repo as a starting point, and attempt to reproduce the results of the A3C method on the continuous action domain, but I am still trying to figure out the network model they used in the physical state case when apply to Mojoco, and how the policy gradient is accumulated.
The text was updated successfully, but these errors were encountered: