Hi,
Me and a friend are working on making an RL LSTM for a video game. However, the rounds can take a while and we were hoping to have one of our (mine) machines run 24/7 (using a VM to allow us to still use our computers as it needs to simulate mouse movement and clicking) and his machine to connect sporadically to also run its own version of the game but contribute to the model learning process.
Is the possible? If not, what is the closest alternative approach?
I have looked through the documentation and while I understand how the current PyTorch distribution packages would work with a given dataset and whatnot, I am not sure how that would work for our use case. Since the model would need to update the parameters after each timestep in the game (each timestep is long, 1 second being the fastest but can be longer). Furthermore, since his computer would connect and disconnect, it would need someway of getting the latest model parameters…
Any advice?