(Tested on Ubuntu 20.04)
- Clone the repo
- Set up a Conda env
- Install OpenSpiel
git clone --recursive [email protected]:indylab/tabular_xdo.git
cd tabular_xdoIf you've already cloned this repo but not the submodules, you can clone them with:
git submodule update --init --recursiveAfter installing Anaconda, enter the repo directory and create the new environment:
conda env create -f environment.yml
conda activate grlDeepMind's OpenSpiel is used for poker game logic as well as tabular game utilities.
# Starting from the repo root
cd dependencies/open_spiel
export BUILD_WITH_ACPC=ON # to compile with the optional universal poker game variant
./install.sh
pip install -e . # This will start a compilation process. Will take a few minutes.
cd ../..Installation is now done!
If you need to compile/recompile OpenSpiel without pip installing it. Perform the following steps with your conda env * active*. (The conda env needs to be active so that OpenSpiel can find and compile against the python development headers in the env. Python version related issues may occur otherwise):
export BUILD_WITH_ACPC=ON # to compile with the optional universal poker game variant
mkdir build
cd build
CXX=clang++ cmake -DPython_TARGET_VERSION=3.6 -DCMAKE_CXX_COMPILER=${CXX} -DPython3_FIND_VIRTUALENV=FIRST -DPython3_FIND_STRATEGY=LOCATION ../open_spiel
make -j$(nproc)
cd ../../..To import OpenSpiel without using pip, add OpenSpiel directories to your PYTHONPATH in your ~ /.bashrc (more details here):
# Add the following lines to your ~/.bashrc:
# For the python modules in open_spiel.
export PYTHONPATH=$PYTHONPATH:/<path_to_open_spiel_submodule>
# For the Python bindings of Pyspiel
export PYTHONPATH=$PYTHONPATH:/<path_to_open_spiel_submodule>/build/pythonTo replicate figure 3.a, run the following commands:
python xdo_psro_fixed_population_comparison.py --num_strats 2
python xdo_psro_fixed_population_comparison.py --num_strats 10
python xdo_psro_fixed_population_comparison.py --num_strats 20
python xdo_psro_fixed_population_comparison.py --num_strats 50
python xdo_psro_fixed_population_comparison.py --num_strats 100
python xdo_psro_fixed_population_comparison.py --num_strats 300
python xdo_psro_fixed_population_comparison.py --num_strats 1000To replicate figure 3.b, run the following commands:
python main_experiments.py --algorithm xdo --game_name leduc_poker
python main_experiments.py --algorithm psro --game_name leduc_pokerTo replicate figure 3.c and figure 4.a, run the following commands:
python main_experiments.py --algorithm xdo --game_name leduc_poker_dummy
python main_experiments.py --algorithm psro --game_name leduc_poker_dummy
python main_experiments.py --algorithm cfr --game_name leduc_poker_dummy
python main_experiments.py --algorithm xfp --game_name leduc_poker_dummy
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent