the network parameters about target critic and critic network

[wallcuber]

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self.target_critic.load_state_dict(critic_state_dict) above code seems make target critic network's parameter always be same as the critic network's. So what is the purpose? making the network learn more slowly？ Hope somebody help me!

[StimulateX]

It seems that the parameters of target_critic network should be updated as target_critic = tau*critic + (1-tau)*target_critic. And the actual critic networks is updated according to gradient of loss function. I am working on this code these days. If I am wrong, please correct it and feel free to contact me.