Cannot create conda environment on Linux with Ubuntu 18.04

[NishanthJKumar]

It seems that the environment.yml file from the repo was made without the --no-builds and --from-history flags (as mentioned here). This makes it impossible to create this environment on another OS like Linux. Adding these flags when exporting the conda environment will hopefully solve the problem, but also may not. For this reason and others, it would be extremely helpful if the authors could use a Docker or Singularity build container for this repo so that others can reproduce results and better study the Imitation Learning method presented!

[Gaoee]

I run goal-gail on my computer with Ubuntu 16.04. Some suggestions hope can help you.
I replace the mujoco license at vendor/mujoco/mjkey.txt, and add a setup.py at the root directory. The environment contains following packages:
absl-py==0.7.0
appnope==0.1.0
astor==0.7.1
atari-py==0.1.1
atomicwrites==1.2.1
attrs==18.2.0
awscli==1.15.4
baselines==0.1.5
bleach==2.1.2
boto3==1.7.4
botocore==1.10.4
Box2D==2.3.2
Box2D-kengz==2.3.3
certifi==2018.8.24
cffi==1.11.4
chardet==3.0.4
click==6.7
cloudpickle==1.1.1
colorama==0.3.7
cycler==0.10.0
Cython==0.28.5
dask==1.1.4
decorator==4.2.1
dill==0.2.8.2
docutils==0.14
dominate==2.3.1
entrypoints==0.2.3
filelock==3.0.8
Flask==0.12.2
future==0.17.1
gast==0.2.2
glfw==1.7.0
google-pasta==0.2.0
grpcio==1.19.0
gtimer==1.0.0b5
gym==0.12.1
h5py==2.7.1
html5lib==0.9999999
idna==2.6
imageio==2.4.1
intel-openmp==2018.0.0
ipykernel==4.8.2
ipython==6.2.1
ipython-genutils==0.2.0
ipywidgets==5.1.5
itsdangerous==0.24
jedi==0.11.1
Jinja2==2.10
jmespath==0.9.3
joblib==0.11
jsonschema==2.6.0
jupyter-client==5.2.2
jupyter-core==4.4.0
Keras-Applications==1.0.7
Keras-Preprocessing==1.0.9
Lasagne==0.1
llvmlite==0.22.0
lockfile==0.12.2
Mako==1.0.7
Markdown==3.0.1
MarkupSafe==1.0
matplotlib==2.1.2
meson==0.48.2
mistune==0.8.3
mkl==2019.0
mock==2.0.0
more-itertools==4.3.0
mpi4py==3.0.0
mujoco-py==1.50.1.56
nbconvert==5.3.1
nbformat==4.4.0
netifaces==0.10.9
networkx==2.1
notebook==5.4.0
numba==0.37.0
numpy==1.18.4
olefile==0.45.1
opencv-python==3.4.3.18
opencv3==4.0.0.21
pandoc==2.0a4
pandoc-min==1.0.9
pandocfilters==1.4.2
parso==0.1.1
path.py==11.0
pathlib2==2.3.2
pbr==3.1.1
pexpect==4.4.0
pickleshare==0.7.4
Pillow==4.2.1
pip==9.0.1
plotly==2.5.0
pluggy==0.7.1
plumbum==1.6.9
ply==3.11
progressbar2==3.38.0
prompt-toolkit==1.0.15
protobuf==3.11.3
ptyprocess==0.5.2
py==1.6.0
pyasn1==0.4.2
pycparser==2.18
pygame==1.9.3
pyglet==1.3.2
Pygments==2.2.0
Pympler==0.6
PyOpenGL==3.1.0
pyparsing==2.2.0
PyPrind==2.11.2
pytest==3.8.0
python-dateutil==2.6.1
python-utils==2.3.0
pytz==2018.3
PyWavelets==0.5.2
PyYAML==3.12
pyzmq==16.0.3
readline==6.2.0
requests==2.18.4
rsa==3.4.2
s3transfer==0.1.13
scikit-image==0.14.2
scikit-learn==0.18.1
scipy==1.4.1
Send2Trash==1.5.0
setuptools==38.5.1
simplegeneric==0.8.1
six==1.11.0
snakeviz==1.0.0
tbb==2020.0.133
tensorboard==1.14.0
tensorflow==1.14.0
tensorflow-estimator==1.14.0
tensorflow-probability==0.6.0
tensorflow-tensorboard==0.1.8
termcolor==1.1.0
terminado==0.8.1
testpath==0.3.1
tflearn==0.3.2
Theano==1.0.1
tk==0.1.0
toolz==0.9.0
torch==0.3.1
torchvision==0.1.9
tornado==4.5.3
tqdm==4.26.0
traitlets==4.3.2
urllib3==1.22
wcwidth==0.1.7
webencodings==0.5.1
Werkzeug==0.14.1
wheel==0.30.0
widgetsnbextension==1.2.3
wrapt==1.12.1
xz==0.0.1
zmq==0.0.0
-e .

[NishanthJKumar]

Thank you Gaoee, this is actually helpful!