malteschilling / ddrl Goto Github PK
View Code? Open in Web Editor NEWDeep Decentralized Reinforcement Learning - locally structured architecture for DRL in a continuous locomotion control task.
License: GNU General Public License v3.0
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how to run and evaluate policies
Dear Malte,
With reference to our conversation in email, I appreciate your kind response. Your research article is very interesting and I am trying to extend it.
I have tried to run a simulation from your repository. I tried to run python3 train_experiment_1_global_reward_on_flat.py. It took a while to complete this simulation. Now, I want to evaluate its results. Could you please elaborate how to evaluate it? I have tried running various python scripts from evaluation folder but I am getting errors. Thank you so much for your response.
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