A game-theoretic approach to provably correct and scalable offline RL

Despite increasingly widespread use of machine learning (ML) in all aspects of our lives, a broad class of scenarios still rely on automation designed by people, not artificial intelligence (AI). In real-world applications that involve making sequences of decisions with long-term consequences, from allocating beds in an intensive-care unit to controlling robots, decision-making strategies to […]

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