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Challenge: NeurIPS 2019 : MineRL Competition
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Challenge: Unity Obstacle Tower Challenge
Does it work properly for everyone else? When I run it for 100 episodes it only saves episodes number 0, 1, 8, 27, 64.
paint_vel_info flag that you can find under
env_config in the .yaml files. There are also some flags that are not in the .yaml files, but people are using (
use_backgrounds). You can find all of them if you scroll down here: https://github.com/openai/procgen .
Should we actually be allowed to change the environment? Maybe these settings should be reset when doing evaluation?
Working Colab example (credit to @tviskaron):
!sudo apt-get purge openjdk-*
!sudo apt-get install openjdk-8-jdk
!pip3 install --upgrade minerl
!sudo apt-get install xvfb xserver-xephyr vnc4server
!sudo pip install pyvirtualdisplay
from pyvirtualdisplay import Display
display = Display(visible=0, size=(640, 480))
env = gym.make(‘MineRLNavigateDense-v0’)
obs = env.reset()
done = False
net_reward = 0
for _ in range(100):
action = env.action_space.noop()
action['camera'] = [0, 0.03*obs["compassAngle"]] action['back'] = 0 action['forward'] = 1 action['jump'] = 1 action['attack'] = 1 obs, reward, done, info = env.step( action) net_reward += reward print("Total reward: ", net_reward)
There was a mention about the final standings for round 2 being based on more seeds than 5 to get a proper average performance. Is that going to happen? I didn’t try to repeatedly submit similar models to overfit the 5 seeds for that reason.
mine says it expires 28 May 2020, not sure if that’s a set date or depends on when you redeem. I can’t find the date of when I redeemed.
Is the debug option off?
0.1, same as a single door (there’s 2 doors in each doorway).
And I was thinking I’m going mad when my previously working submission suddenly broke after “disabling” debug
Can’t wait! I’ve been trying to get my dopamine trained agent to be scored (only 5-7 floors so far), but the only response I get after every change is
The following containers terminated prematurely. : agent
and it’s not very helpful. It builds fine, but gets stuck on evaluation phase.
In the Obstacle Tower paper there is a section on human performance. 15 people tried it multiple times and the max floor was 22. Am I reading this right? I finished all 25 floors on my very first try without much trouble.
How far did everyone else get and how many runs did you do? We could try collecting more data and make a more accurate human benchmark this way.