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The goal of this issue would be to investigate the possibility of de-coupling the model used to make desicions (value assignment) from the model that is being updated. As of now, the backpropagation occurs at every update_freq time steps (after update_freq decisions). When the model is being updated by the backpropagation, the trajectory generation must stop. However, as the trajectory generation is done one sample at a time, there is a lot of space remaining on the GPU to compute the backprop asynchronously. Doing this would allow us to generate more trajectories and possibly speed up the resolution of problems
The text was updated successfully, but these errors were encountered:
The goal of this issue would be to investigate the possibility of de-coupling the model used to make desicions (value assignment) from the model that is being updated. As of now, the backpropagation occurs at every
update_freq
time steps (afterupdate_freq
decisions). When the model is being updated by the backpropagation, the trajectory generation must stop. However, as the trajectory generation is done one sample at a time, there is a lot of space remaining on the GPU to compute the backprop asynchronously. Doing this would allow us to generate more trajectories and possibly speed up the resolution of problemsThe text was updated successfully, but these errors were encountered: