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Public repo for agent code for AAAI20 paper Theory-based Causal Transfer: Integrating Instance-level Induction and Abstract-level Structure Learning
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openlockagents initial commite Nov 27, 2019
.gitignore initial commite Nov 27, 2019
README.md
__init__.py
logger.py
requirements.txt
setup.py

README.md

OpenLock Learner

This repo contains the code for the agents in the AAAI 2020 Oral paper "Theory-based Causal Transfer: Integrating Instance-level Induction and Abstract-level Structure Learning." For the paper and additional details, please see the project page.

It provides various agents to use with the OpenLock OpenAI Gym environment

You'll need to bring in the OpenLock repo into your PYTHONPATH for this repo. If you are using a virtualenv, you can add export PYTHONPATH="/path/to/OpenLock" to /bin/activate. Alternatively, you can python setup.py install OpenLock to add it as a package to your python environment.

If you use this repo, please cite our work:

@inproceedings{edmonds2020theory,
  title={Theory-based Causal Transfer: Integrating Instance-level Induction and Abstract-level Structure Learning},
  author={Edmonds, Mark and Ma, Xiaojian and Qi, Siyuan, and Zhu, Yixin and Lu, Hongjing and Zhu, Song-Chun},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  year={2020}
}
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