This is the repository for the project of the course Computational Semantics for Natural Language Processing at ETH Spring Semester 2021.

Our project is named CARL: Corpus-Augmented Reinforcement Learning by

Batuhan Tomekce, Ege Karaismailoglu, Harish Rajagopal, Johannes Dollinger

In order to reproduce our results first the environment needs to be set up.

1. Install NLE from here
2. Install torchbeast here
3. Clone this repo and install the dependencies in here
4. Now you can run polyhydra with bsub -W 23:50 -n 20 -R "rusage[ngpus_excl_p=8]" -R "select[gpu_model0==GeForceGTX1080Ti]" python polyhydra.py
5. You can change the subtask and parameters from the config

├── nethack_baselines             # Baseline agents for submission
│    ├── other_examples  	
│    ├── rllib	                  # Baseline agent trained with rllib
│    └── torchbeast               # Baseline agent trained with IMPALA on Pytorch
│    │   └── polyhydra.py         # The code to run experiments
│    │   └── config.yaml          # File to change the hyperparameters and the environment to train