Probability trees and the value of a single intervention. (arXiv:2205.08779v1 [cs.LG])

The most fundamental problem in statistical causality is determining causal
relationships from limited data. Probability trees, which combine prior causal
structures with Bayesian updates, have been suggested as a possible solution.
In this work, we quantify the information gain from a single intervention and
show that both the anticipated information gain, prior to making an
intervention, and the expected gain from an intervention have simple
expressions. This results in an active-learning method that simply selects the
intervention with the highest …

arxiv probability trees value