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07/22/2023
HIQL: Offline Goal-Conditioned RL with Latent States as Actions
Unsupervised pre-training has recently become the bedrock for computer v...
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04/10/2023
Reinforcement Learning from Passive Data via Latent Intentions
Passive observational data, such as human videos, is abundant and rich i...
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10/06/2022
Distributionally Adaptive Meta Reinforcement Learning
Meta-reinforcement learning algorithms provide a data-driven way to acqu...
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07/05/2022
Offline RL Policies Should be Trained to be Adaptive
Offline RL algorithms must account for the fact that the dataset they ar...
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07/13/2021
Why Generalization in RL is Difficult: Epistemic POMDPs and Implicit Partial Observability
Generalization is a central challenge for the deployment of reinforcemen...
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10/27/2020
Implicit Under-Parameterization Inhibits Data-Efficient Deep Reinforcement Learning
We identify an implicit under-parameterization phenomenon in value-based...
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07/10/2020
Representations for Stable Off-Policy Reinforcement Learning
Reinforcement learning with function approximation can be unstable and e...
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02/28/2020
On Catastrophic Interference in Atari 2600 Games
Model-free deep reinforcement learning algorithms are troubled with poor...
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12/12/2019
Learning To Reach Goals Without Reinforcement Learning
Imitation learning algorithms provide a simple and straightforward appro...
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11/19/2018
Learning Actionable Representations with Goal-Conditioned Policies
Representation learning is a central challenge across a range of machine...
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05/29/2018
Variational Inverse Control with Events: A General Framework for Data-Driven Reward Definition
The design of a reward function often poses a major practical challenge ...
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11/27/2017