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Use this tag for questions related to "hyperbolic tangent activation functions" (tanh) used in neural networks.
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Could we add clipping in the output layer of the actor in DDPG?
action)
4 store action, state and reward
5 if the number of experiences is larger than L:
6 update the parameters of the agent
In this case, the actor NN that predicts the DDPG has a $\tanh … My question is, could we add the clipping in the output layer of the actor (changing $\tanh(x)$ by $\operatorname{clip}(a\cdot \tanh(x)+b, x, y$) in the training loop? …