Abstracts: NeurIPS 2024 with Dylan Foster
DYLAN FOSTER: Thanks for having me. TINGLE: Let’s start with a brief overview of this paper. Tell us about the problem this work addresses and why the research community should know about it. FOSTER: So this is a, kind of, a theoretical work on reinforcement learning, or RL. When I say reinforcement learning, broadly speaking, this is talking about the question of how can we design AI agents that are capable of, like, interacting with unknown environments and learning how […]
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