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05/26/2023
Future-conditioned Unsupervised Pretraining for Decision Transformer
Recent research in offline reinforcement learning (RL) has demonstrated ...
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02/05/2023
Sample Dropout: A Simple yet Effective Variance Reduction Technique in Deep Policy Optimization
Recent success in Deep Reinforcement Learning (DRL) methods has shown th...
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11/08/2022
Pretraining in Deep Reinforcement Learning: A Survey
The past few years have seen rapid progress in combining reinforcement l...
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09/21/2022
Revisiting Discrete Soft Actor-Critic
We study the adaption of soft actor-critic (SAC) from continuous action ...
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09/01/2022
Dynamics-Adaptive Continual Reinforcement Learning via Progressive Contextualization
A key challenge of continual reinforcement learning (CRL) in dynamic env...
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02/17/2022
MineRL Diamond 2021 Competition: Overview, Results, and Lessons Learned
Reinforcement learning competitions advance the field by providing appro...
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12/07/2021
JueWu-MC: Playing Minecraft with Sample-efficient Hierarchical Reinforcement Learning
Learning rational behaviors in open-world games like Minecraft remains t...
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06/09/2021
Joint System-Wise Optimization for Pipeline Goal-Oriented Dialog System
Recent work (Takanobu et al., 2020) proposed the system-wise evaluation ...
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06/16/2020
Model-based Adversarial Meta-Reinforcement Learning
Meta-reinforcement learning (meta-RL) aims to learn from multiple traini...
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11/06/2019
Distributional Reward Decomposition for Reinforcement Learning
Many reinforcement learning (RL) tasks have specific properties that can...
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11/05/2019
Fully Parameterized Quantile Function for Distributional Reinforcement Learning
Distributional Reinforcement Learning (RL) differs from traditional RL i...
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05/19/2018