Spring 2022 GRASP SFI: Jason Ma, University of Pennsylvania, “Beyond Expected Reward in Offline Reinforcement Learning”
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Levine 512
*This will be a HYBRID Event with in-person attendance in Levine 512 and Virtual attendance via Zoom Offline reinforcement learning (RL), which uses pre-collected, reusable offline data without further environment interactions, permits sample-efficient, scalable and practical decision-making; however, most of the existing literature (1) focuses on improving algorithms for maximizing the expected cumulative reward, and (2) […]

