Contextual-Gridworld

This repository hosts the Contextual Grid-world environment used for the experiments in

Hamid Eghbal-zadeh*, Florian Henkel* and Gerhard Widmer
"Learning to Infer Unseen Contexts in Causal Contextual Reinforcement Learning"
Self-supervision for Reinforcement Learning (SSL-RL) Workshop ICLR, 2021, Vienna, Austria

Setup and Requirements

First, clone the project from github.

git clone https://github.com/eghbalz/contextual-gridworld.git

Navigate to the directory

cd contextual-gridworld

As a next step you need to install the required packages. If your are an anaconda user, we provide an anaconda environment file which can be installed as follows:

conda env create -f environment.yml

Activate your conda environment:

source activate contextual_gridworld

and install the contextual_gridworld package in develop mode:

python setup.py develop --user

To verify that everything is working, try to run python manual_control.py in the contextual_gridworld directory. You can control the agent using the arrow keys UP, LEFT and RIGHT.

Citation

@InProceedings{pmlr-v148-eghbal-zadeh21a,
  title     =  {Context-Adaptive Reinforcement Learning using Unsupervised Learning of Context Variables},
  author    =  {Eghbal-zadeh, Hamid and Henkel, Florian and Widmer, Gerhard},
  booktitle =  {NeurIPS 2020 Workshop on Pre-registration in Machine Learning},
  pages     =  {236--254},
  year      =  {2021},
  editor    =  {Bertinetto, Luca and Henriques, João F. and Albanie, Samuel and Paganini, Michela and Varol, Gül},
  volume    =  {148},
  series    =  {Proceedings of Machine Learning Research},
  month     =  {11 Dec},
  publisher =  {PMLR},
  pdf       =  {http://proceedings.mlr.press/v148/eghbal-zadeh21a/eghbal-zadeh21a.pdf},
  url       =  {http://proceedings.mlr.press/v148/eghbal-zadeh21a.html}
}

@InProceedings{eghbal2021learning,
  title={Learning to Infer Unseen Contexts in Causal Contextual Reinforcement Learning},
  author={Eghbal-zadeh, Hamid and Henkel, Florian and Widmer, Gerhard},
  booktitle={Self-supervision for Reinforcement Learning (SSL-RL),  ICLR 2021 Workshop},
  year={2021}
}