Comments (4)
You can install xvfb, sudo apt-get install xvfb
and then run this command:
xvfb-run -s "-screen 0 1400x900x24" bash
and then run the code.
See here: https://github.com/openai/gym#rendering-on-a-server
from noreward-rl.
Yes, I use this way by reading your 'README.md' and can run it on my server. But the speed is still low, Given a perfect path, mario needs 5 seconds to pass the level 1. Besides, when I reset the environment, it will open a new fceux and does not kill the old one, I will get more than 100 fceux after a few minutes, could you tell me how you solve this when training?
from noreward-rl.
@shinshiner how many a3c workers are you using? Yes, fceux simulator isn't super friendly to work with but it should not "hard" reset 100 times in few minutes. Something is wrong. You are using fceux in different xvfb screens, right?
from noreward-rl.
I use 8-10 workers, and I have solved the fceux problem, but when I trained for about 4 hours, whatever message I send to env, it just did nothing and the whole processes were like 'down'.
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Related Issues (20)
- Use this model with demo frames
- 安装报错
- a GAN idea HOT 1
- Feature normalization ?
- Question: I want to run a single worker HOT 2
- Tryinf to run simple atari pong HOT 1
- Convergence without LSTM
- Inconsistent actions between train and inference on Mario
- Questions about training
- Tried to run demo.py got syntax error HOT 3
- Generate maze code
- Could the algorithm be used on reinforced learning algorithms with experience reply?
- extrinsic and intrinsic combination HOT 1
- Failed to build doom-py HOT 2
- RuntimeError: go_vncdriver must be imported before tensorflow
- Tensor Board Version
- models.tar.gz cannot be downloaded HOT 3
- Update Code to Tensorflow 2.0
- What is the compatible python version?
- tensor flow not compatible and check sum issue in the requirement file
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from noreward-rl.