Learning Dynamic Knowledge Graphs to Generalize on Text-based Games

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Code for paper Learning Dynamic Knowledge Graphs to Generalize on Text-based Games.

# Dependencies
conda create -p /tmp/gata python=3.6 numpy scipy ipython matplotlib cython nltk pillow
source activate /tmp/gata
pip install --upgrade pip
pip install numpy==1.16.2
pip install gym==0.15.4
pip install textworld
pip install -U spacy
python -m spacy download en
pip install tqdm pipreqs h5py pyyaml visdom
conda install pytorch torchvision cudatoolkit=9.2 -c pytorch

Pretraining Action Prediction / State Prediction / Deep Graph Infomax / Command Generation

# Word embeddings
wget "https://bit.ly/2U3Mde2"

# Action Prediction
cd ap.0.2 ; wget https://aka.ms/twkg/ap.0.2.zip ; unzip ap.0.2.zip ; cd ..
# Modify config.yaml
python train_action_prediction.py

# Deep Graph Infomax
cd dgi.0.2 ; wget https://aka.ms/twkg/dgi.0.2.zip ; unzip dgi.0.2.zip ; cd ..
# Modify config.yaml
python train_deep_graph_infomax.py

# State Prediction
cd sp.0.2 ; wget https://aka.ms/twkg/sp.0.2.zip ; unzip sp.0.2.zip ; cd ..
# Modify config.yaml
python train_state_prediction.py

# Command generation
cd cmd_gen.0.2 ; wget https://aka.ms/twkg/cmd_gen.0.2.zip ; unzip cmd_gen.0.2.zip ; cd ..
# Modify config.yaml
python train_command_generation.py config.yaml

Training RL agents

# Download games
cd rl.0.1 ; wget https://aka.ms/twkg/rl.0.1.zip ; unzip rl.0.1.zip ; cd ..

# Modify config.yaml
python train_rl.py config.yaml

Monitoring training progress

To monitor training progress: set "visdom: True" in config.yaml under the general section, and start Visdom in another terminal using the visdom command line. Then, open the link displayed by Visdom in your browser.

Citation

Please use the following bibtex entry:

@article{adhikari2020gata,
  title={Learning Dynamic Knowledge Graphs to Generalize on Text-based Games},
  author={Adhikari, Ashutosh and Yuan, Xingdi and C\^ot\'{e}, Marc-Alexandre and Zelinka, Mikul\'{a}\v{s} and Rondeau, Marc-Antoine and Laroche, Romain and Poupart, Pascal and Tang, Jian and Trischler, Adam and Hamilton, William L.},
  journal={CoRR},
  volume={abs/2002.09127},
  year= {2020},
  archivePrefix={arXiv},
  eprint={2002.09127}
}

License

MIT