Cover Image

An Empirical Study on the Effectiveness of Incorporating Offline RL As Online RL Subroutines

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Su, Jianhai, Luo, Jinzhu, Zhang, Qi
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Policy Agnostic RL: Offline RL and Online RL Fine-Tuning of Any Class and Backbone
by: Mark, Max Sobol, et al.
Published: (2024)

Budgeting Counterfactual for Offline RL
by: Liu, Yao, et al.
Published: (2023)

Action-Free Offline-to-Online RL via Discretised State Policies
by: Neggatu, Natinael Solomon, et al.
Published: (2026)

Dual Alignment Maximin Optimization for Offline Model-based RL
by: Zhou, Chi, et al.
Published: (2025)

Selective Uncertainty Propagation in Offline RL
by: Krishnamurthy, Sanath Kumar, et al.
Published: (2023)

Decoupled Prioritized Resampling for Offline RL
by: Yue, Yang, et al.
Published: (2023)

Augmenting Offline RL with Unlabeled Data
by: Wang, Zhao, et al.
Published: (2024)

Robust Policy Expansion for Offline-to-Online RL under Diverse Data Corruption
by: He, Longxiang, et al.
Published: (2025)

SortedRL: Accelerating RL Training for LLMs through Online Length-Aware Scheduling
by: Zhang, Yiqi, et al.
Published: (2026)

Design Considerations in Offline Preference-based RL
by: Agarwal, Alekh, et al.
Published: (2025)

A Tractable Inference Perspective of Offline RL
by: Liu, Xuejie, et al.
Published: (2023)

Are Expressive Models Truly Necessary for Offline RL?
by: Wang, Guan, et al.
Published: (2024)

OGBench: Benchmarking Offline Goal-Conditioned RL
by: Park, Seohong, et al.
Published: (2024)

Offline vs. Online Learning in Model-based RL: Lessons for Data Collection Strategies
by: Chen, Jiaqi, et al.
Published: (2025)

Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuning
by: Nakamoto, Mitsuhiko, et al.
Published: (2023)

An Empirical Risk Minimization Approach for Offline Inverse RL and Dynamic Discrete Choice Model
by: Kang, Enoch H., et al.
Published: (2025)

Efficient Online RL Fine Tuning with Offline Pre-trained Policy Only
by: Xiao, Wei, et al.
Published: (2025)

Online Finetuning Decision Transformers with Pure RL Gradients
by: Luo, Junkai, et al.
Published: (2026)

Yes, Q-learning Helps Offline In-Context RL
by: Tarasov, Denis, et al.
Published: (2025)

Scalable Offline Model-Based RL with Action Chunks
by: Park, Kwanyoung, et al.
Published: (2025)

Offline Multi-task Transfer RL with Representational Penalization
by: Bose, Avinandan, et al.
Published: (2024)

Is Value Learning Really the Main Bottleneck in Offline RL?
by: Park, Seohong, et al.
Published: (2024)

The Role of Deep Learning Regularizations on Actors in Offline RL
by: Tarasov, Denis, et al.
Published: (2024)

H2O+: An Improved Framework for Hybrid Offline-and-Online RL with Dynamics Gaps
by: Niu, Haoyi, et al.
Published: (2023)

Offline RL with Smooth OOD Generalization in Convex Hull and its Neighborhood
by: Yao, Qingmao, et al.
Published: (2025)

Offline RLAIF: Piloting VLM Feedback for RL via SFO
by: Beck, Jacob
Published: (2025)

Integrating Domain Knowledge for handling Limited Data in Offline RL
by: Gangopadhyay, Briti, et al.
Published: (2024)

Language-Conditioned Offline RL for Multi-Robot Navigation
by: Morad, Steven, et al.
Published: (2024)

Offline-Boosted Actor-Critic: Adaptively Blending Optimal Historical Behaviors in Deep Off-Policy RL
by: Luo, Yu, et al.
Published: (2024)

Failure-Aware RL: Reliable Offline-to-Online Reinforcement Learning with Self-Recovery for Real-World Manipulation
by: Li, Huanyu, et al.
Published: (2026)

GAS: Enhancing Reward-Cost Balance of Generative Model-assisted Offline Safe RL
by: Liu, Zifan, et al.
Published: (2026)

HIQL: Offline Goal-Conditioned RL with Latent States as Actions
by: Park, Seohong, et al.
Published: (2023)

STO-RL: Offline RL under Sparse Rewards via LLM-Guided Subgoal Temporal Order
by: Gu, Chengyang, et al.
Published: (2026)

Reinforcement Learning with Euclidean Data Augmentation for State-Based Continuous Control
by: Luo, Jinzhu, et al.
Published: (2024)

Toward Explainable Offline RL: Analyzing Representations in Intrinsically Motivated Decision Transformers
by: Guiducci, Leonardo, et al.
Published: (2025)

Chain-of-Goals Hierarchical Policy for Long-Horizon Offline Goal-Conditioned RL
by: Choi, Jinwoo, et al.
Published: (2026)

OMG-RL:Offline Model-based Guided Reward Learning for Heparin Treatment
by: Lim, Yooseok, et al.
Published: (2024)

Stabilizing Contrastive RL: Techniques for Robotic Goal Reaching from Offline Data
by: Zheng, Chongyi, et al.
Published: (2023)

ReFORM: Reflected Flows for On-support Offline RL via Noise Manipulation
by: Zhang, Songyuan, et al.
Published: (2026)

DEAS: DEtached value learning with Action Sequence for Scalable Offline RL
by: Kim, Changyeon, et al.
Published: (2025)