-
Notifications
You must be signed in to change notification settings - Fork 2
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Environment not registered in OpenAI Gym #1
Comments
Also, when I changed it to Using TensorFlow backend. |
I'm using Python 3.5 so I think it was an import issue But this new error comes and I can't file assets folder Using TensorFlow backend. |
That's possibly an issue, believe I had to stick with
Okay so that exists in https://github.com/mryellow/maze_explorer/tree/master/mazeexp/engine/assets ... Have seen this error before, guess it's a dev/production environment issue. That part should be including the assets files, confirmed they show in the distribution zip file... I'll see if I can duplicate it and fix the build config. A work-around which should work would be to clone the gym and environment repo, then I was able to get it working with adding
Although classic DQN has trouble with the reward function phrased how it is currently (where only apples/poison/walls have rewards but no constant proximity signal like Karpathy used). Not certain the memory config is making it into agent with current build, complains about |
Deployed a new version |
Thank you for the help! I'll check it out and let you know. I'm working on Deep RL for maze solving and I think this project has great potential as a benchmark environment |
I see the apples/poison thing as being very similar to DeepMind's Labyrinth but with a much smaller input state space, making it good for smaller/faster experiments. Think really need to reign in the default reward function for benchmark use, something easily learnable which provides meaningful scores or reward graph. Currently running with Has been handy running it this way for discovering bugs in velocity code or wall collisions, but think need to cut all those "running into a wall" experiences by setting a terminal flag and having more prioritised experiences relating to finding apples rather than avoiding walls. I'll do a few more experiments between these wall rewards and Karpathy's wall proximity based reward. Aiming for something which can be effectively trained on a classic DQN without A3C (his proximity reward results in smooth forward reward seeking behaviour after 1m experiences, where wall reward can result in a lot of spinning in circles). Then when it comes to reward functions which are a little more rarely rewarding (like second exploration/escape game mode) there is some A3C testing needed. However I had TF |
Hi
I would really like to use this environment for Deep RL reserach purposes. But I'm not able to get it to work. Please help. Thanks
Using TensorFlow backend.
[2017-08-28 17:41:07,956] Making new env: MazeExplorer-v0
Traceback (most recent call last):
File "/home/USERNAME/anaconda2/envs/tensorflow35/lib/python3.5/site-packages/gym/envs/registration.py", line 137, in spec
return self.env_specs[id]
KeyError: 'MazeExplorer-v0'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/USERNAME/PycharmProjects/MazeExplorer/MazeTest.py", line 5, in
env = gym.make('MazeExplorer-v0')
File "/home/USERNAME/anaconda2/envs/tensorflow35/lib/python3.5/site-packages/gym/envs/registration.py", line 161, in make
return registry.make(id)
File "/home/USERNAME/anaconda2/envs/tensorflow35/lib/python3.5/site-packages/gym/envs/registration.py", line 118, in make
spec = self.spec(id)
File "/home/USERNAME/anaconda2/envs/tensorflow35/lib/python3.5/site-packages/gym/envs/registration.py", line 147, in spec
raise error.UnregisteredEnv('No registered env with id: {}'.format(id))
gym.error.UnregisteredEnv: No registered env with id: MazeExplorer-v0
Process finished with exit code 1
The text was updated successfully, but these errors were encountered: