668 citations · 2.1k across the 23 of their papers we have counts for
4 papers · 1 filter
Deep neuroethology of a virtual rodent
Josh Merel, Diego Aldarondo, Jesse Marshall +3
Parallel developments in neuroscience and deep learning have led to mutually productive exchanges, pushing our understanding of real and artificial neural networks in sensory and c…
Catch & Carry: Reusable Neural Controllers for Vision-Guided Whole-Body Tasks
Josh Merel, Saran Tunyasuvunakool, Arun Ahuja +6
We address the longstanding challenge of producing flexible, realistic humanoid character controllers that can perform diverse whole-body tasks involving object interactions. This…
Modelling Generalized Forces with Reinforcement Learning for Sim-to-Real Transfer
Rae Jeong, Jackie Kay, Francesco Romano +6
Learning robotic control policies in the real world gives rise to challenges in data efficiency, safety, and controlling the initial condition of the system. On the other hand, sim…
Learning Gentle Object Manipulation with Curiosity-Driven Deep Reinforcement Learning
Sandy H. Huang, Martina Zambelli, Jackie Kay +4
Robots must know how to be gentle when they need to interact with fragile objects, or when the robot itself is prone to wear and tear. We propose an approach that enables deep rein…