166 citations · 274 across the 26 of their papers we have counts for
3 papers · 1 filter
Diffusion Augmented Agents: A Framework for Efficient Exploration and Transfer Learning
Norman Di Palo, Leonard Hasenclever, Jan Humplik +1
We introduce Diffusion Augmented Agents (DAAG), a novel framework that leverages large language models, vision language models, and diffusion models to improve sample efficiency an…
Learning Robot Soccer from Egocentric Vision with Deep Reinforcement Learning
Dhruva Tirumala, Markus Wulfmeier, Ben Moran +13
We apply multi-agent deep reinforcement learning (RL) to train end-to-end robot soccer policies with fully onboard computation and sensing via egocentric RGB vision. This setting r…
Real-World Fluid Directed Rigid Body Control via Deep Reinforcement Learning
Mohak Bhardwaj, Thomas Lampe, Michael Neunert +6
Recent advances in real-world applications of reinforcement learning (RL) have relied on the ability to accurately simulate systems at scale. However, domains such as fluid dynamic…