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Reinforcement Learning on Musculoskeletal Models
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Sample-efficient reinforcement learning in Minecraft
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A new benchmark for Artificial Intelligence (AI) research in Reinforcement Learning
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NeurIPS 2019: Learn to Move - Walk Around
Questions about evaluation set up
Over 4 years agoIβve investigated such a difference was claimed by my mistake in observation preprocessing, not taking the order difference into attention.
BTW, even after fixing 140-150 mean score got to approx. 20 by the cause of difference in initial state for evaluation environment. Hope, now there would be no such issueβ¦
Different reward on local and remote environments
Over 4 years agoWhile trying to commit the solution obtaining completely different scores(~5 vs 100-180) on remote environment comparing to local one.
Local is osim-rl 3.0.6, which seems to be the latest.
Model setup is round 1 - difficulty 2, model=β3Dβ
How could that be?
Questions about evaluation set up
Over 4 years ago@smsong, BTW, Iβve just received more than 100 mean reward for my local environment with all default Round 1 properties, and when submitted at server environment - got exactly 52 steps at each run and 5 mean reward in total.
How could that be possible?
Let me know, if you need any specific info to investigate.
Maximal repository weight for Docker-commit
Over 4 years agoHello, may you say what is the repo volume limit for docker commit?
Iβve tried to push 70mbs repo with my model files, but it failed.
I suppose limit is 50 mbs?
If so - could we obtain model files using wget or something?