pascal (probabilistic inductive constraint logic) is a new pack containing an algorithm for learning probabilistic integrity constraints. It was proposed in
Fabrizio Riguzzi, Elena Bellodi, Riccardo Zese, Marco Alberti, and Evelina Lamma. Probabilistic inductive constraint logic. Machine Learning, 110:723–754, 2021. doi:10.1007/s10994-020-05911-6
It contains modules for both structure and parameter learning.
You can find the manual at http://friguzzi.github.io/pascal/.
You can try it online at http://cplint.eu.
In particular, see the example at https://cplint.eu/e/pascal_examples.swinb
Best
Fabrizio