I was trying to replicate the essay "Human-level control through deep reinforcement learning"(https://www.nature.com/articles/nature14236), but the code it provided is not available. So I tried to find the corresponding code in GitHub. And the new question is the repositories are too old.(https://github.com/devsisters/DQN-tensorflow) (https://github.com/jihoonerd/Human-level-control-through-deep-reinforcement-learning) the first one requires tensorflow0.12.0, but the oldest version of python that my anaconda supports is 3.6.0(on which tensorflow0.12.0 cannot work), so I tried the second one but the packages in requirements.txt always conflict with each other.
For the second repositories, I tried to install the correct versions. but I still cannot run the code
How to make the code runnable? Or are there any other resources of the code of the paper?
I used venv in conda with python==3.7.0 and following packages:
absl-py==0.15.0
argon2-cffi==23.1.0
argon2-cffi-bindings==21.2.0
astor==0.8.0
astroid==2.7.3
astunparse==1.6.3
atari-py==0.2.6
atomicwrites==1.3.0
attrs==19.2.0
backcall==0.1.0
bleach==3.3.0
cachetools==5.3.3
certifi @ file:///C:/b/abs_85o_6fm0se/croot/certifi_1671487778835/work/certifi
cffi==1.15.1
charset-normalizer==3.3.2
click==8.1.7
cloudpickle==1.2.2
colorama==0.4.6
cycler==0.10.0
decorator==4.4.0
defusedxml==0.6.0
entrypoints==0.3
flatbuffers==1.12
flit_core @ file:///opt/conda/conda-bld/flit-core_1644941570762/work/source/flit_core
future==0.17.1
gast==0.3.3
google-auth==2.28.2
google-auth-oauthlib==0.4.6
google-pasta==0.2.0
grpcio==1.32.0
gym==0.26.2
gym-notices==0.0.8
h5py==2.10.0
idna==3.6
imageio==2.6.1
importlib-metadata==6.7.0
importlib-resources==5.12.0
ipykernel==5.1.2
ipython==7.9.0
ipython-genutils==0.2.0
ipywidgets==7.5.1
isort==4.3.21
jedi==0.15.1
Jinja2==2.10.1
jsonschema==3.0.2
jupyter==1.0.0
jupyter-client==5.3.4
jupyter-console==6.0.0
jupyter-core==4.6.1
Keras-Applications==1.0.8
Keras-Preprocessing==1.1.2
kiwisolver==1.1.0
lazy-object-proxy==1.4.2
libtorrent==2.0.9
logger==1.4
Markdown==3.1.1
MarkupSafe==1.1.1
matplotlib==3.1.1
mccabe==0.6.1
mistune==0.8.4
mkl-fft==1.3.1
mkl-random @ file:///C:/ci/mkl_random_1626186163140/work
mkl-service==2.4.0
more-itertools==7.2.0
nbconvert==5.6.0
nbformat==4.4.0
networkx==2.3
notebook==6.1.5
numpy==1.19.5
oauthlib==3.2.2
opencv-python==4.1.2.30
opt-einsum==3.3.0
packaging==19.2
pandocfilters==1.4.2
parso==0.5.1
pexpect==4.7.0
pickleshare==0.7.5
Pillow==9.5.0
platformdirs==2.6.1
pluggy==0.13.0
prometheus-client==0.7.1
prompt-toolkit==2.0.9
protobuf==3.9.2
ptyprocess==0.6.0
py==1.8.0
pyasn1==0.5.1
pyasn1-modules==0.3.0
pycparser==2.21
pyglet==1.3.2
Pygments==2.4.2
pylint==2.10.2
pyparsing==2.4.2
pyrsistent==0.15.4
pytest==5.0.1
python-dateutil==2.8.0
pytz @ file:///C:/b/abs_22fofvpn1x/croot/pytz_1671698059864/work
PyWavelets==1.0.3
pywin32==306
pywinpty==2.0.10
pyzmq==18.1.1
qtconsole==4.5.5
requests==2.31.0
requests-oauthlib==1.4.0
rsa==4.9
scipy==1.3.2
Send2Trash==1.5.0
sip==4.19.13
six==1.15.0
tensorboard==2.8.0
tensorboard-data-server==0.6.1
tensorboard-plugin-wit==1.8.1
tensorflow-estimator==2.4.0
tensorflow-gpu==2.4.0
termcolor==1.1.0
terminado==0.8.3
testpath==0.4.2
toml==0.10.2
tornado==6.0.3
tqdm==4.66.2
traitlets==4.3.2
typed-ast==1.4.0
typing-extensions==3.7.4.3
urllib3==2.0.7
wcwidth==0.1.7
webencodings==0.5.1
Werkzeug==0.16.0
widgetsnbextension==3.5.1
wincertstore==0.2
wrapt==1.12.1
zipp==3.15.0