An overview of the quantitative causality analysis and causal graph reconstruction based on a rigorous formalism of information flow

Abstract

Inference of causal relations from data now has become an important field in artificial intelligence. During the past 16 years, causality analysis (in a quantitative sense) has been developed independently in physics from first principles. This short note is a brief summary of this line of work, including part of the theory and several representative applications.

arXiv comment7 pages, 1 figure. Presented at the First International AIxIA Workshop on Causality, Causal-ITALY, Italian Conference on Artificial Intelligence, November 30, 2021