Spring 2025 GRASP SFI: Qinghua Liu, Microsoft Research, “When Is Partially Observable Reinforcement Learning Not Scary?”
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Levine 307
3330 Walnut Street, Philadelphia, PA, United States
This will be a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom. ABSTRACT Partial observability is ubiquitous in Reinforcement Learning (RL) applications, where agents must make sequential decisions despite lacking complete information about the latent states of the controlled system. Partially observable RL is notoriously challenging in theory—well-known information-theoretic results […]


