WhatIf

A solver for counterfactual inference over probabilistic logic programs.

WhatIf based on the aspmc library for probabilistic logic programming inference.

Its main functionality is the translation of counterfactual queries to marginal queries.

For usage on Linux you may install this software as a pip package via

pip install counterfactuals

Examples for command line usage are available below.

If you have any issues please contact us, or even better create an issue on GitHub.

For academic usage cite

• Kiesel, R., Rückschloß, K., & Weitkämper, F. (2023, July). "What if?" in Probabilistic Logic Programming. In Proceedings of the 39th International Conference on Logic Programming.

Development setup

For developement clone via

git clone git@github.com:raki123/counterfactuals.git

We require Python >= 3.6.

All required modules are listed in requirements.txt and can be obtained by running

pip install -r requirements.txt

To use WhatIf as usual but have changes to the code available run

pip install -e .

in the root directory of this repository.

Usage

The basic usage is

WhatIf [-e .] [-ds .] [-dt .] [-k .] [-v .] [-h] [<INPUT-FILES>]
    --knowlege          -k  COMPILER    set the knowledge compiler to COMPILER:
                                        * sharpsat-td       : uses a compilation version of sharpsat-td (default)
                                        * d4                : uses the (slightly modified) d4 compiler. 
                                        * c2d               : uses the c2d compiler. 
                                        * miniC2D           : uses the miniC2D compiler. 
                                        * pysdd             : uses the PySDD compiler. 
    --evidence          -e  NAME,VALUE  add evidence NAME:
                                        * the evidence is not negated if VALUE is `True`.
                                        * the evidence is negated if VALUE is `False`.
    --intervene         -i  NAME,VALUE  intervene on NAME:
                                        * the intervention is not negated if VALUE is `True`.
                                        * the intervention is negated if VALUE is `False`.
    --query             -q  NAME        query for the probability of NAME.
    --decos             -ds SOLVER      set the solver that computes tree decompositions to SOLVER:
                                        * flow-cutter       : uses flow_cutter_pace17 (default)
    --decot             -dt SECONDS     set the timeout for computing tree decompositions to SECONDS (default: 1)
    --verbosity         -v  VERBOSITY   set the logging level to VERBOSITY:
                                        * debug             : print everything
                                        * info              : print as usual
                                        * result            : only print results, warnings and errors
                                        * warning           : only print warnings and errors
                                        * errors            : only print errors
    --help              -h              print this help and exit

Examples

When using the pip package replace python main.py by WhatIf to obtain the same result.

ASP example:

python main.py -q slippery -e sprinkler,True -i sprinkler,False -k sharpsat-td
0.5::u1.
0.7::u2.
0.1::u3.
0.6::u4.
szn_spr_sum :- u1.
sprinkler :- szn_spr_sum, u2.
rain :- szn_spr_sum, u3.
rain :- \+szn_spr_sum, u4.
wet :- rain.
wet :- sprinkler.
slippery :- wet.

Reads the sprinkler program from stdin and adds evidence sprinkler and intervention \+sprinkler. The query is for slippery.

This results in the output

[WARNING] aspmc: Query for atom true was proven true during grounding.
[WARNING] aspmc: Including it has a negative impact on performance.
[INFO] aspmc: Tree Decomposition #bags: 18 unfolded treewidth: 3 #vertices: 20
[INFO] aspmc: Preprocessing disabled
[INFO] aspmc:    Stats Compilation
[INFO] aspmc: ------------------------------------------------------------
[INFO] aspmc: Compilation time:         0.005887508392333984
[INFO] aspmc: Counting time:            0.0001952648162841797
[INFO] aspmc: ------------------------------------------------------------
[INFO] WhatIf:    Results
[INFO] WhatIf: ------------------------------------------------------------
[RESULT] WhatIf: slippery:             0.09999999999999999

telling us that the result of the counterfactual query for slippery is 0.1.

The first two lines are a warning from aspmc that tell us that the atom true that we included to compute the probability of the evidence may lead to decreased performance. However, we need to include it as its probability is not 1.0 in general.

The following info lines tell us some stats about the program and the inference:

• it has a treewidth upper bound of 3
• aspmc's preprocessing is disabled
• knowledge compilation took ~0.006 seconds
• counting over the resulting circuit took ~0.0002 seconds