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License: MIT License
Reinforcement learning for deep brain stimulation (DBS) modeling
License: MIT License
Hello,
Nice project =)
I created a colab notebook to try it online directly: https://colab.research.google.com/drive/19bdAiKZY0r5OR3gEv7164CjDOdMRGYqt
Btw, why didn't you use deterministic=True
for the prediction? (this would suppress the exploration noise)
Quick question: did you try other algorithms that are usually more suited for continuous actions? (like soft actor-critic (SAC), DDPG and TD3 which should be more sample efficient too)
We would also be interested if you could do a pull request on stable-baselines where you add your project to the documentation (project section) ;)
PS: I tried with SAC (with parameters from the original paper) on on your environment and I could get (apparently) good results in 2e5 steps, the plot:
And the ratio of stds:
>print(np.sqrt(s))
1509
Hello! Can't run the repo because there is not file with all dependencies. Also, I've noticed that the version of python you've written in read.me is 3.6., but in jupyter notebook the warning message in the very first cell is from python 3.7.
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