swMATH ID: 22924
Software Authors: Riguzzi, Fabrizio; Cota, Giuseppe; Bellodi, Elena; Zese, Riccardo
Description: Causal inference in cplint. cplint is a suite of programs for reasoning and learning with Probabilistic Logic Programming languages that follow the distribution semantics. In this paper we describe how we have extended cplint to perform causal reasoning. In particular, we consider Pearl’s do calculus for models where all the variables are measured. The two cplint modules for inference, PITA and MCINTYRE, have been extended for computing the effect of actions/interventions on these models. We also executed experiments comparing exact and approximate inference with conditional and causal queries, showing that causal inference is often cheaper than conditional inference.
Homepage: https://github.com/friguzzi/cplint
Source Code: https://github.com/friguzzi/cplint
Keywords: probabilistic logic programming; distribution semantics; logic programs with annotated disjunctions; problog; causal inference; statistical relational artificial intelligence
Related Software: ProbLog; SWI-Prolog; PRISM; XSB; PITA; CP-logic; MCINTYRE; Aleph; DeepProbLog; SCIFF; PrASP; SOLAR; PRMLT; RelNN; Metaopt; Tuffy; Adam; PIDoc; SWISH DataLab; IPython
Cited in: 6 Publications

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1 Publication describing the Software, including 1 Publication in zbMATH Year
Causal inference in cplint. Zbl 1419.68034
Riguzzi, Fabrizio; Cota, Giuseppe; Bellodi, Elena; Zese, Riccardo

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