Guided Data Augmentation for Offline Reinforcement Learning and Imitation Learning
Fuente:
arXiv
Saved in:
| Main Authors: | Corrado, Nicholas E., Qu, Yuxiao, Balis, John U., Labiosa, Adam, Hanna, Josiah P. |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Multi-Robot Collaboration through Reinforcement Learning and Abstract Simulation
by: Labiosa, Adam, et al.
Published: (2025)
by: Labiosa, Adam, et al.
Published: (2025)
Understanding when Dynamics-Invariant Data Augmentations Benefit Model-Free Reinforcement Learning Updates
by: Corrado, Nicholas E., et al.
Published: (2023)
by: Corrado, Nicholas E., et al.
Published: (2023)
On-Policy Policy Gradient Reinforcement Learning Without On-Policy Sampling
by: Corrado, Nicholas E., et al.
Published: (2023)
by: Corrado, Nicholas E., et al.
Published: (2023)
Trajectory-Level Data Augmentation for Offline Reinforcement Learning
by: Schmähling, Tobias, et al.
Published: (2026)
by: Schmähling, Tobias, et al.
Published: (2026)
Distributionally Robust Multi-Task Reinforcement Learning via Adaptive Task Sampling
by: Corrado, Nicholas E., et al.
Published: (2026)
by: Corrado, Nicholas E., et al.
Published: (2026)
Using Non-Expert Data to Robustify Imitation Learning via Offline Reinforcement Learning
by: Huang, Kevin, et al.
Published: (2025)
by: Huang, Kevin, et al.
Published: (2025)
Reinforcement Learning Within the Classical Robotics Stack: A Case Study in Robot Soccer
by: Labiosa, Adam, et al.
Published: (2024)
by: Labiosa, Adam, et al.
Published: (2024)
Goal-Conditioned Data Augmentation for Offline Reinforcement Learning
by: Huang, Xingshuai, et al.
Published: (2024)
by: Huang, Xingshuai, et al.
Published: (2024)
Reinforcement Learning via Auxiliary Task Distillation
by: Harish, Abhinav Narayan, et al.
Published: (2024)
by: Harish, Abhinav Narayan, et al.
Published: (2024)
Centralized Adaptive Sampling for Reliable Co-Training of Independent Multi-Agent Policies
by: Corrado, Nicholas E., et al.
Published: (2025)
by: Corrado, Nicholas E., et al.
Published: (2025)
Equivariant Offline Reinforcement Learning
by: Tangri, Arsh, et al.
Published: (2024)
by: Tangri, Arsh, et al.
Published: (2024)
An Introduction to Deep Reinforcement and Imitation Learning
by: Santana, Pedro
Published: (2025)
by: Santana, Pedro
Published: (2025)
Offline Imitation Learning Through Graph Search and Retrieval
by: Yin, Zhao-Heng, et al.
Published: (2024)
by: Yin, Zhao-Heng, et al.
Published: (2024)
Offline Imitation Learning upon Arbitrary Demonstrations by Pre-Training Dynamics Representations
by: Ma, Haitong, et al.
Published: (2025)
by: Ma, Haitong, et al.
Published: (2025)
Variable-Speed Teaching-Playback as Real-World Data Augmentation for Imitation Learning
by: Masuya, Nozomu, et al.
Published: (2024)
by: Masuya, Nozomu, et al.
Published: (2024)
Learning to Drive by Imitating Surrounding Vehicles
by: Sonmez, Yasin, et al.
Published: (2025)
by: Sonmez, Yasin, et al.
Published: (2025)
Safe Offline Reinforcement Learning with Feasibility-Guided Diffusion Model
by: Zheng, Yinan, et al.
Published: (2024)
by: Zheng, Yinan, et al.
Published: (2024)
Adaptive Advantage-Guided Policy Regularization for Offline Reinforcement Learning
by: Liu, Tenglong, et al.
Published: (2024)
by: Liu, Tenglong, et al.
Published: (2024)
FlowRetrieval: Flow-Guided Data Retrieval for Few-Shot Imitation Learning
by: Lin, Li-Heng, et al.
Published: (2024)
by: Lin, Li-Heng, et al.
Published: (2024)
RILe: Reinforced Imitation Learning
by: Albaba, Mert, et al.
Published: (2024)
by: Albaba, Mert, et al.
Published: (2024)
Tube-NeRF: Efficient Imitation Learning of Visuomotor Policies from MPC using Tube-Guided Data Augmentation and NeRFs
by: Tagliabue, Andrea, et al.
Published: (2023)
by: Tagliabue, Andrea, et al.
Published: (2023)
Off-Dynamics Reinforcement Learning via Domain Adaptation and Reward Augmented Imitation
by: Guo, Yihong, et al.
Published: (2024)
by: Guo, Yihong, et al.
Published: (2024)
FlowQ: Energy-Guided Flow Policies for Offline Reinforcement Learning
by: Alles, Marvin, et al.
Published: (2025)
by: Alles, Marvin, et al.
Published: (2025)
Temporal Distance-aware Transition Augmentation for Offline Model-based Reinforcement Learning
by: Lee, Dongsu, et al.
Published: (2025)
by: Lee, Dongsu, et al.
Published: (2025)
A Dual Approach to Imitation Learning from Observations with Offline Datasets
by: Sikchi, Harshit, et al.
Published: (2024)
by: Sikchi, Harshit, et al.
Published: (2024)
Residual Learning and Context Encoding for Adaptive Offline-to-Online Reinforcement Learning
by: Nakhaei, Mohammadreza, et al.
Published: (2024)
by: Nakhaei, Mohammadreza, et al.
Published: (2024)
Augmented Reality Demonstrations for Scalable Robot Imitation Learning
by: Yang, Yue, et al.
Published: (2024)
by: Yang, Yue, et al.
Published: (2024)
Adaptive Q-Chunking for Offline-to-Online Reinforcement Learning
by: Gireesh, Nandiraju, et al.
Published: (2026)
by: Gireesh, Nandiraju, et al.
Published: (2026)
An Imitative Reinforcement Learning Framework for Pursuit-Lock-Launch Missions
by: Li, Siyuan, et al.
Published: (2024)
by: Li, Siyuan, et al.
Published: (2024)
T2S: Tokenized Skill Scaling for Lifelong Imitation Learning
by: Zhang, Hongquan, et al.
Published: (2025)
by: Zhang, Hongquan, et al.
Published: (2025)
DataMIL: Selecting Data for Robot Imitation Learning with Datamodels
by: Dass, Shivin, et al.
Published: (2025)
by: Dass, Shivin, et al.
Published: (2025)
SPREAD: Subspace Representation Distillation for Lifelong Imitation Learning
by: Roy, Kaushik, et al.
Published: (2026)
by: Roy, Kaushik, et al.
Published: (2026)
JUICER: Data-Efficient Imitation Learning for Robotic Assembly
by: Ankile, Lars, et al.
Published: (2024)
by: Ankile, Lars, et al.
Published: (2024)
A Real-World Quadrupedal Locomotion Benchmark for Offline Reinforcement Learning
by: Zhang, Hongyin, et al.
Published: (2023)
by: Zhang, Hongyin, et al.
Published: (2023)
Q-value Regularized Decision ConvFormer for Offline Reinforcement Learning
by: Yan, Teng, et al.
Published: (2024)
by: Yan, Teng, et al.
Published: (2024)
Offline Reinforcement Learning with Discrete Diffusion Skills
by: Qiao, RuiXi, et al.
Published: (2025)
by: Qiao, RuiXi, et al.
Published: (2025)
Improving Offline Reinforcement Learning with Inaccurate Simulators
by: Hou, Yiwen, et al.
Published: (2024)
by: Hou, Yiwen, et al.
Published: (2024)
A Clean Slate for Offline Reinforcement Learning
by: Jackson, Matthew Thomas, et al.
Published: (2025)
by: Jackson, Matthew Thomas, et al.
Published: (2025)
SGN-CIRL: Scene Graph-based Navigation with Curriculum, Imitation, and Reinforcement Learning
by: Oskolkov, Nikita, et al.
Published: (2025)
by: Oskolkov, Nikita, et al.
Published: (2025)
Causal Flow Q-Learning for Robust Offline Reinforcement Learning
by: Li, Mingxuan, et al.
Published: (2026)
by: Li, Mingxuan, et al.
Published: (2026)
Similar Items
-
Multi-Robot Collaboration through Reinforcement Learning and Abstract Simulation
by: Labiosa, Adam, et al.
Published: (2025) -
Understanding when Dynamics-Invariant Data Augmentations Benefit Model-Free Reinforcement Learning Updates
by: Corrado, Nicholas E., et al.
Published: (2023) -
On-Policy Policy Gradient Reinforcement Learning Without On-Policy Sampling
by: Corrado, Nicholas E., et al.
Published: (2023) -
Trajectory-Level Data Augmentation for Offline Reinforcement Learning
by: Schmähling, Tobias, et al.
Published: (2026) -
Distributionally Robust Multi-Task Reinforcement Learning via Adaptive Task Sampling
by: Corrado, Nicholas E., et al.
Published: (2026)