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dbuse avatar dbuse commented on May 30, 2024

Hi @nazisu2020,

the observation space is defined via *.gym_connection.observation_space in the omnetpp.ini file and transmitted to the env object when the Veins/OMNeT++ simulation connects to it. This way, the definition only depends on the scenario/environment and the veins-gym library can stay agnostic.

I guess you have changed or removed this parameter somehow...

Best,
Dominik

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nazisu2020 avatar nazisu2020 commented on May 30, 2024

Hi @dbuse ,

Thanks for your quick reply, firstly.

But there is no changed in this tutorial ipynb file, I just via git clone https://github.com/tkn-tub/serpentine-env put this code into VsCode and via Jupyter Extension for Visual Studio Code to run this .ipynb file.

Maybe if it has something to do with the version of omnet++/veins/protoc/sumo... I use?

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dbuse avatar dbuse commented on May 30, 2024

That is strange. Does the same error appear if you run the random agent script instead of the Jupyter notebook?

You could also try to enable debug output of Veins or run Veins separately to see if there is any error when starting Veins.

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dbuse avatar dbuse commented on May 30, 2024

Please update VeinsGym to 0.3.3+ and seee if the error persists. Also see #8.

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nazisu2020 avatar nazisu2020 commented on May 30, 2024

Hi @dbuse ,
Thanks for your advices!

I will try based on your suggestion.

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nazisu2020 avatar nazisu2020 commented on May 30, 2024

Hi @dbuse
After I update VeinsGym to the new 0.3.3 version, I can run this tutorial example,
Thank you very much!!

But there is a UserWarning in the process of running env.reset(), which should not affect it, right?

(veins) na@na-Precision-5820-Tower:~/workspace/serpentine-env$ /home/na/.conda/envs/veins/bin/python /home/na/workspace/serpentine-env/examples/random_agent.py
/home/na/.conda/envs/veins/lib/python3.9/site-packages/gym/utils/passive_env_checker.py:223: UserWarning: WARN: The default seed argument in `Env.reset` should be `None`, otherwise the environment will by default always be deterministic
  logger.warn(
Number of steps taken: 3680
Mean reward: 0.6732228221518555

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dbuse avatar dbuse commented on May 30, 2024

Yeah, that is only relevant for future interfaces. Happy I could help.

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