380 citations · 725 across the 16 of their papers we have counts for
3 papers · 1 filter
PopGen: Generating Semantically Diverse Populations for Zero-Shot Coordination
Paul Teiletche, Kanghyun Ryu, Kyungjoon Park +3
In multi-agent reinforcement learning, exposing a cooperator to partners with diverse strategies during training is key to better collaboration at test time. However, existing meth…
HuGo: LLMs as Whole-Body Policy Code Designers for Humanoid Loco-Manipulation
Seoyeon Choi, Shizhao Ye, Nicholas Bui +5
For humanoids to be useful in everyday environments, they must perform a wide range of tasks that couple locomotion and manipulation. Existing approaches commonly acquire a loco-ma…
What Matters for Simulation to Online Reinforcement Learning on Real Robots
Yarden As, Dhruva Tirumala, René Zurbrügg +4
We investigate what specific design choices enable successful online reinforcement learning (RL) on physical robots. Across 100 real-world training runs on three distinct robotic p…