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01/18/2023
Human-Timescale Adaptation in an Open-Ended Task Space
Foundation models have shown impressive adaptation and scalability in su...
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09/22/2022
Developing, Evaluating and Scaling Learning Agents in Multi-Agent Environments
The Game Theory Multi-Agent team at DeepMind studies several aspects...
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01/27/2022
The Challenges of Exploration for Offline Reinforcement Learning
Offline Reinforcement Learning (ORL) enablesus to separately study the t...
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12/10/2021
Zero-Shot Uncertainty-Aware Deployment of Simulation Trained Policies on Real-World Robots
While deep reinforcement learning (RL) agents have demonstrated incredib...
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09/17/2021
Is Curiosity All You Need? On the Utility of Emergent Behaviours from Curious Exploration
Curiosity-based reward schemes can present powerful exploration mechanis...
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07/21/2021
Bayesian Controller Fusion: Leveraging Control Priors in Deep Reinforcement Learning for Robotics
We present Bayesian Controller Fusion (BCF): a hybrid control strategy t...
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10/07/2020
Learning Arbitrary-Goal Fabric Folding with One Hour of Real Robot Experience
Manipulating deformable objects, such as fabric, is a long standing prob...
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03/11/2020
Multiplicative Controller Fusion: A Hybrid Navigation Strategy For Deployment in Unknown Environments
Learning-based approaches often outperform hand-coded algorithmic soluti...
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11/20/2019
Evaluating task-agnostic exploration for fixed-batch learning of arbitrary future tasks
Deep reinforcement learning has been shown to solve challenging tasks wh...
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10/09/2019
Ctrl-Z: Recovering from Instability in Reinforcement Learning
When learning behavior, training data is often generated by the learner ...
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09/20/2018
