Code for paper: Matching a Desired Causal State via Shift Interventions (NeurIPS 2021).
arXiv link: https://arxiv.org/abs/2107.01850
To generate a causal system along with its desired mean, run the following for example:
python generate.py --sampler 'barbasi_albert' --nnodes 100 --sparse 10 --dataset_size 1
To generate multiple instances with same parameters (e.g., number of nodes and DAG type), set dataset_size to be larger than 1.
To run a policy on a .pkl file of problem instances, e.g., clique tree policy with single perturbation target interventions:
python test_policy.py ./data/barbasi_albert/nodes100_int10.pkl --sparse 1 --policy clique --results_dir results/barbasi_albert
For interventions with multiple perturbation targets, set sparse to be larger than 1. Supported policy: random, clique, submodular, oracle, structure.