521 citations · 1.2k across the 41 of their papers we have counts for
5 papers · 1 filter
EXIMO: VLM Guided Exploration of VLA Policies
Bhavya Sukhija, Oliver Groth, Mohit Shridhar +5
How to efficiently finetune robot policies to learn new tasks on the fly? State of the art robotic manipulation policies are based on behaviour cloning of large vision-language-act…
Game On: Towards Language Models as RL Experimenters
Jingwei Zhang, Thomas Lampe, Abbas Abdolmaleki +2
We propose an agent architecture that automates parts of the common reinforcement learning experiment workflow, to enable automated mastery of control domains for embodied agents.…
From Motor Control to Team Play in Simulated Humanoid Football
Siqi Liu, Guy Lever, Zhe Wang +19
Intelligent behaviour in the physical world exhibits structure at multiple spatial and temporal scales. Although movements are ultimately executed at the level of instantaneous mus…
V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control
H. Francis Song, Abbas Abdolmaleki, Jost Tobias Springenberg +11
Some of the most successful applications of deep reinforcement learning to challenging domains in discrete and continuous control have used policy gradient methods in the on-policy…
DeepMind Control Suite
Yuval Tassa, Yotam Doron, Alistair Muldal +9
The DeepMind Control Suite is a set of continuous control tasks with a standardised structure and interpretable rewards, intended to serve as performance benchmarks for reinforceme…