counterfactual-inference

This paper formalises counterfactual policy optimisation for Markov Decision Processes under probabilistic nondeterministic causal models, which separate latent confounding from inherent stochasticity, and proposes a practical optimisation procedure for deriving robust counterfactual policies. The approach is validated on a sepsis treatment simulator with diabetes as an unobserved global confounder.