InfoVis Final Project.
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execute backend server.
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$ cd backend $ yarn start
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execute frontend server.
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$ cd backend/frontend $ yarn start
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explore!
- tensorflow==1.13.1
- sklearn
- gym
- mujoco-py
- matplotlib
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$ cd SAC $ ./train.sh
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After few minutes, the policy learning rate version is trained, and the visualization web is updated.
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To get more information about train arguments, you can execute "python main.py -h".