This is a modified version of the causal structure learning algorithm called Relational Causal Discovery (RCD). This version facilitates the experiments provided in the paper titled Learning Relational Causal Models with Cycles through Relational Acyclification. The original RCD implementation was released here which is no longer available. A working copy of the original software can be found here.

conda env create -f conda_venv_rcd.yml

It will create a conda venv named "rcd" which will contain all the required packages. You need to activate the venv before using it:

source activate rcd

• Run Oracle example:

  python src/runOracleRCD.py

• Run Database Example:

  • Configure Postgres database and load the dump file src/rcd-test-data.sql

  • Then run the following:

    python src/runDatabaseRCD.py

References

Ragib Ahsan, David Arbour, Elena Zheleva (2023) Learning Relational Causal Models with Cycles through Relational Acyclification. In Proceedings of Thirty-sixth AAAI Conference on Artificial Intelligence (AAAI 2023).

Ragib Ahsan, David Arbour, Elena Zheleva (2022) Relational Causal Models with Cycle: Representation and Reasoning. In Proceedings of 1st Conference on Causal Learning and Representation (CLeaR 2016).

Sanghack Lee and Vasant Honavar (2016) On Learning Causal Models for Relational Data. In Proceedings of Thirtieth AAAI Conference on Artificial Intelligence (AAAI 2016).

Marc Maier, Katerina Marazopoulou, David Arbour, and David Jensen (2013) A sound and complete algorithm for learning causal models from relational data. In Proceedings of the Twenty-Ninth UAI Conference on Uncertainty in Artificial Intelligence, (UAI-2013)