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03/07/2023
Structured State Space Models for In-Context Reinforcement Learning
Structured state space sequence (S4) models have recently achieved state...
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02/28/2023
Hierarchical Reinforcement Learning in Complex 3D Environments
Hierarchical Reinforcement Learning (HRL) agents have the potential to d...
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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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11/08/2020
On the role of planning in model-based deep reinforcement learning
Model-based planning is often thought to be necessary for deep, careful ...
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07/27/2020
Learning Compositional Neural Programs for Continuous Control
We propose a novel solution to challenging sparse-reward, continuous con...
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06/01/2020
Acme: A Research Framework for Distributed Reinforcement Learning
Deep reinforcement learning has led to many recent-and groundbreaking-ad...
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05/19/2020
Privileged Information Dropout in Reinforcement Learning
Using privileged information during training can improve the sample effi...
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12/18/2019
Analysing Deep Reinforcement Learning Agents Trained with Domain Randomisation
Deep reinforcement learning has the potential to train robots to perform...
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09/12/2019
Modular Meta-Learning with Shrinkage
Most gradient-based approaches to meta-learning do not explicitly accoun...
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11/08/2018
