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References (52)

[1]
Reinforcement Learning via Implicit Imitation Guidance
2025Perry Dong, Alec M. Lessing et al.
[2]
CHEQ-ing the Box: Safe Variable Impedance Learning for Robotic Polishing
2025Emma Cramer, Lukas Jäschke et al.
[3]
Efficient and Stable Offline-to-online Reinforcement Learning via Continual Policy Revitalization
2024Rui Kong, Chenyang Wu et al.
[4]
Gymnasium: A Standard Interface for Reinforcement Learning Environments
2024Mark Towers, Ariel Kwiatkowski et al.
[5]
Foundation Policies with Hilbert Representations
2024Seohong Park, Tobias Kreiman et al.
[6]
FlowPG: Action-constrained Policy Gradient with Normalizing Flows
2024J. Brahmanage, Jiajing Ling et al.
[7]
Generative Modelling of Stochastic Actions with Arbitrary Constraints in Reinforcement Learning
2023Changyu Chen, Ramesha Karunasena et al.
[8]
Imitation Bootstrapped Reinforcement Learning
2023Hengyuan Hu, Suvir Mirchandani et al.
[9]
DrM: Mastering Visual Reinforcement Learning through Dormant Ratio Minimization
2023Guowei Xu, Ruijie Zheng et al.
[10]
Demonstration-Regularized RL
2023D. Tiapkin, D. Belomestny et al.
[11]
METRA: Scalable Unsupervised RL with Metric-Aware Abstraction
2023Seohong Park, Oleh Rybkin et al.
[12]
Prioritized Soft Q-Decomposition for Lexicographic Reinforcement Learning
2023Finn Rietz, Stefan Heinrich et al.
[13]
Efficient Online Reinforcement Learning with Offline Data
2023Philip J. Ball, Laura M. Smith et al.
[14]
Policy Expansion for Bridging Offline-to-Online Reinforcement Learning
2023Haichao Zhang, Weiwen Xu et al.
[15]
Residual Skill Policies: Learning an Adaptable Skill-based Action Space for Reinforcement Learning for Robotics
2022Krishan Rana, Ming Xu et al.
[16]
Adaptive Behavior Cloning Regularization for Stable Offline-to-Online Reinforcement Learning
2022Yi Zhao, Rinu Boney et al.
[17]
MPR-RL: Multi-Prior Regularized Reinforcement Learning for Knowledge Transfer
2022Quantao Yang, J. A. Stork et al.
[18]
The Primacy Bias in Deep Reinforcement Learning
2022Evgenii Nikishin, Max Schwarzer et al.
[19]
Augmenting Reinforcement Learning with Behavior Primitives for Diverse Manipulation Tasks
2021Soroush Nasiriany, Huihan Liu et al.
[20]
A Minimalist Approach to Offline Reinforcement Learning
2021Scott Fujimoto, S. Gu

Showing 20 of 52 references

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