67 citations · 191 across the 16 of their papers we have counts for
4 papers · 1 filter
Vision-Language Models as a Source of Rewards
Kate Baumli, Satinder Baveja, Feryal Behbahani +24
Building generalist agents that can accomplish many goals in rich open-ended environments is one of the research frontiers for reinforcement learning. A key limiting factor for bui…
Structured State Space Models for In-Context Reinforcement Learning
Chris Lu, Yannick Schroecker, Albert Gu +4
Structured state space sequence (S4) models have recently achieved state-of-the-art performance on long-range sequence modeling tasks. These models also have fast inference speeds…
Hierarchical Reinforcement Learning in Complex 3D Environments
Bernardo Avila Pires, Feryal Behbahani, Hubert Soyer +3
Hierarchical Reinforcement Learning (HRL) agents have the potential to demonstrate appealing capabilities such as planning and exploration with abstraction, transfer, and skill reu…
Human-Timescale Adaptation in an Open-Ended Task Space
Adaptive Agent Team, Jakob Bauer, Kate Baumli +25
Foundation models have shown impressive adaptation and scalability in supervised and self-supervised learning problems, but so far these successes have not fully translated to rein…