gym.error.Error: Attempted to look up malformed environment ID: b'DARC-master'. (Currently all IDs must be of the form ^(?:[\w:-]+\/)?([\w:.-]+)-v(\d+)$.)

[Doraemonprogrammer]

When I run this command, I get this error, what is the problem?Is there any solution?I have been configuring the environment for this project for a week, and it has not succeeded, can you tell me how to configure the project environment?

python main.py --env <environment_name> --save-model --policy DARC --dir ./logs/DARC/r1 --seed 1 --qweight 0.1 --reg 0.005

error： gym.error.Error: Attempted to look up malformed environment ID: b'DARC-master'. (Currently all IDs must be of the form ^(?:[\w:-]+/)?([\w:.-]+)-v(\d+)$.)

[dmksjfl]

Hi, to the best of my knowledge, this error occurs when you use a self-defined environment instead of a standard built-in Gym environments. The following links seem to be relevant and you can check it out!

https://github.com/openai/gym/issues/1514

https://stackoverflow.com/questions/53602382/register-openai-gym-malformed-environment-failure

If you run the commands on a Gym environment and get similar errors, please let me know. For example,

python main.py --env Hopper-v2 --save-model --policy DARC --dir ./logs/DARC/r1 --seed 1 --qweight 0.1 --reg 0.005

[Doraemonprogrammer]

Name Version Build Channel

_libgcc_mutex 0.1 main https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main _openmp_mutex 5.1 1_gnu https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main absl-py 2.1.0 pypi_0 pypi alabaster 0.7.13 pypi_0 pypi babel 2.14.0 pypi_0 pypi backcall 0.2.0 pypi_0 pypi box2d-py 2.3.8 pypi_0 pypi ca-certificates 2024.2.2 hbcca054_0 conda-forge certifi 2024.2.2 pyhd8ed1ab_0 conda-forge cffi 1.15.1 pypi_0 pypi charset-normalizer 3.3.2 pypi_0 pypi cloog 0.18.0 0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free cloudpickle 1.6.0 pypi_0 pypi cython 0.29.37 pypi_0 pypi decorator 5.1.1 pypi_0 pypi docutils 0.19 pypi_0 pypi exceptiongroup 1.2.0 pypi_0 pypi expat 2.4.8 h27087fc_0 conda-forge farama-notifications 0.0.4 pypi_0 pypi fasteners 0.19 pypi_0 pypi future 1.0.0 pypi_0 pypi gcc 4.8.5 7 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free glew 2.1.0 h9c3ff4c_2 conda-forge glfw 2.7.0 pypi_0 pypi glfw3 3.2.1 0 menpo gmp 6.1.0 0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free gym 0.18.0 pypi_0 pypi gym-notices 0.0.8 pypi_0 pypi gymnasium 0.28.1 pypi_0 pypi idna 3.6 pypi_0 pypi imagehash 4.3.1 pypi_0 pypi imageio 2.9.0 pypi_0 pypi imagesize 1.4.1 pypi_0 pypi importlib-metadata 6.7.0 pypi_0 pypi iniconfig 2.0.0 pypi_0 pypi ipdb 0.13.13 pypi_0 pypi ipython 7.34.0 pypi_0 pypi isl 0.12.2 0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free jax-jumpy 1.0.0 pypi_0 pypi jedi 0.19.1 pypi_0 pypi jinja2 3.1.3 pypi_0 pypi ld_impl_linux-64 2.38 h1181459_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main libffi 3.3 he6710b0_2 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main libgcc-ng 11.2.0 h1234567_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main libglu 9.0.0 he1b5a44_1001 conda-forge libgomp 11.2.0 h1234567_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main libstdcxx-ng 11.2.0 h1234567_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main libxcb 1.12 1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free lockfile 0.12.2 pypi_0 pypi markupsafe 2.1.5 pypi_0 pypi matplotlib-inline 0.1.6 pypi_0 pypi mesalib 18.3.1 h590aaf7_0 conda-forge mpc 1.0.3 0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free mpfr 3.1.5 0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free mujoco-py 2.1.2.14 pypi_0 pypi ncurses 6.4 h6a678d5_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main numpy 1.21.6 pypi_0 pypi numpydoc 1.5.0 pypi_0 pypi openssl 1.1.1o h166bdaf_0 conda-forge packaging 23.2 pypi_0 pypi parso 0.8.3 pypi_0 pypi patchelf 0.17.2.1 pypi_0 pypi pexpect 4.9.0 pypi_0 pypi pickleshare 0.7.5 pypi_0 pypi pillow 7.2.0 pypi_0 pypi pip 22.3.1 py37h06a4308_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main pluggy 1.2.0 pypi_0 pypi prompt-toolkit 3.0.43 pypi_0 pypi protobuf 4.24.4 pypi_0 pypi ptyprocess 0.7.0 pypi_0 pypi pybullet 3.2.6 pypi_0 pypi pybulletgym 0.1 dev_0 pycparser 2.21 pypi_0 pypi pyglet 1.5.0 pypi_0 pypi pygments 2.17.2 pypi_0 pypi pyopengl 3.1.7 pypi_0 pypi pytest 7.4.4 pypi_0 pypi pytest-instafail 0.3.0 pypi_0 pypi python 3.7.9 h7579374_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main pytz 2024.1 pypi_0 pypi pywavelets 1.3.0 pypi_0 pypi readline 8.2 h5eee18b_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main requests 2.31.0 pypi_0 pypi scipy 1.7.3 pypi_0 pypi setuptools 65.6.3 py37h06a4308_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main snowballstemmer 2.2.0 pypi_0 pypi sphinx 5.3.0 pypi_0 pypi sphinx-rtd-theme 2.0.0 pypi_0 pypi sphinxcontrib-applehelp 1.0.2 pypi_0 pypi sphinxcontrib-devhelp 1.0.2 pypi_0 pypi sphinxcontrib-htmlhelp 2.0.0 pypi_0 pypi sphinxcontrib-jquery 4.1 pypi_0 pypi sphinxcontrib-jsmath 1.0.1 pypi_0 pypi sphinxcontrib-qthelp 1.0.3 pypi_0 pypi sphinxcontrib-serializinghtml 1.1.5 pypi_0 pypi sqlite 3.38.2 hc218d9a_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main tensorboardx 2.6.2.2 pypi_0 pypi tk 8.6.11 h1ccaba5_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main tomli 2.0.1 pypi_0 pypi torch 1.8.0 pypi_0 pypi traitlets 5.9.0 pypi_0 pypi typing-extensions 4.7.1 pypi_0 pypi urllib3 2.0.7 pypi_0 pypi wcwidth 0.2.13 pypi_0 pypi wheel 0.38.4 py37h06a4308_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main xorg-kbproto 1.0.7 h7f98852_1002 conda-forge xorg-libx11 1.6.12 h36c2ea0_0 conda-forge xorg-libxext 1.3.4 h516909a_0 conda-forge xorg-xextproto 7.3.0 h7f98852_1002 conda-forge xorg-xproto 7.0.31 h7f98852_1007 conda-forge xz 5.4.6 h5eee18b_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main zipp 3.15.0 pypi_0 pypi zlib 1.2.11 0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free

I installed the environment in the readme via pip，including “pip install gym==0.18.0". Can you elaborate on how to deploy the project environment?

[dmksjfl]

It seems you have already prepared all the packages needed to run the codes.

First, please make sure that you can import mujoco_py without errors in python. Please also make sure that mujoco is installed and the path is added in the .bashrc (also remember to source the .bashrc file). Then, please make sure that you can successfully make Gym environments and can interact with the environment. For a quick test, you can run the following testing codes:

import gym
env = gym.make('Hopper-v2')
state = env.reset()
action = env.action_space.sample()
env.step(action)

If all these are ready and prepared, the DARC agent can be trained by calling:

python main.py --env Hopper-v2 --save-model --policy DARC --dir ./logs/DARC/r1 --seed 1 --qweight 0.1 --reg 0.005

Can you run DARC on Gym environments like Hopper-v2?

[Doraemonprogrammer]

I've installed and imported mujoco correctly. /home/jayking/图片/2024-03-23 11-34-51 的屏幕截图.png

when I run main.py file, it returns the following error. Traceback (most recent call last): File "/home/jayking/桌面/paper/2 (PWC)Efficient Continuous Control with Double Actors and Regularized Critics/DARC-master/main.py", line 158, in eval_return = eval_policy(policy, args.env, args.seed, eval_cnt=eval_cnt) NameError: name 'policy' is not defined

When I run the following command in the pycharm terminal python main.py --env DARC-master --save-model --policy DARC --dir ./logs/DARC/r1 --seed 1 --qweight 0.1 --reg 0.005 DARC-master is my virtual environment name. It returns the following error. gym.error.Error: Attempted to look up malformed environment ID: b'DARC-master'. (Currently all IDs must be of the form ^(?:[\w:-]+/)?([\w:.-]+)-v(\d+)$.)

import gym
env = gym.make('Hopper-v2')
state = env.reset()
action = env.action_space.sample()
env.step(action)

I tested as you provided the command and there were no errors. It output
(array([ 1.25174789e+00, 9.83464941e-04, 8.57300138e-04, -5.43328104e-03, -9.26288475e-03, 1.01797468e-02, -5.32635501e-02, 6.97706286e-01, 9.26560873e-01, -1.17996963e-01, -1.29647609e+00]), 1.0034917395753498, False, {})

[dmksjfl]

Hi, when running this repo in pycharm, you ought not to specify the env_name as DARC-master, but the specified task name, e.g., Hopper-v2. Please try following:

python main.py --env Hopper-v2 --save-model --policy DARC --dir ./logs/DARC/r1 --seed 1 --qweight 0.1 --reg 0.005

Meanwhile, the referenced code seems to be line 152 in our repo instead of line 158 (it seems you add some other codes, please check your codes!), see https://github.com/dmksjfl/DARC/blob/112ddf7944bc57482ad8d9eb58a9affcc1037abe/main.py#L152C28-L152C34

For a quick check, please return back to the original version, This error occurs as the policy is not defined. If you use our original code and specify the policy as --policy DARC, the policy should get defined.