Probabilistic Reasoning across the Causal Hierarchy release_y35w6gyjybhsnevhujmlzieju4

by Duligur Ibeling, Thomas Icard

Released as a article .

2021  

Abstract

We propose a formalization of the three-tier causal hierarchy of association, intervention, and counterfactuals as a series of probabilistic logical languages. Our languages are of strictly increasing expressivity, the first capable of expressing quantitative probabilistic reasoning -- including conditional independence and Bayesian inference -- the second encoding do-calculus reasoning for causal effects, and the third capturing a fully expressive do-calculus for arbitrary counterfactual queries. We give a corresponding series of finitary axiomatizations complete over both structural causal models and probabilistic programs, and show that satisfiability and validity for each language are decidable in polynomial space.
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Type  article
Stage   submitted
Date   2021-06-02
Version   v5
Language   en ?
arXiv  2001.02889v5
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