Causal Markov Decision Processes: Learning Good Interventions Efficiently

15 Feb 2021 Yangyi Lu Amirhossein Meisami Ambuj Tewari

We introduce causal Markov Decision Processes (C-MDPs), a new formalism for sequential decision making which combines the standard MDP formulation with causal structures over state transition and reward functions. Many contemporary and emerging application areas such as digital healthcare and digital marketing can benefit from modeling with C-MDPs due to the causal mechanisms underlying the relationship between interventions and states/rewards... (read more)

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