Cover Image

Sample-Efficient Policy Constraint Offline Deep Reinforcement Learning based on Sample Filtering

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Chen, Yuanhao, Liu, Qi, Chen, Pengbin, Qiao, Zhongjian, Li, Yanjie
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Efficient Cross-Domain Offline Reinforcement Learning with Dynamics- and Value-Aligned Data Filtering
by: Qiao, Zhongjian, et al.
Published: (2025)

SUMO: Search-Based Uncertainty Estimation for Model-Based Offline Reinforcement Learning
by: Qiao, Zhongjian, et al.
Published: (2024)

When is Offline Policy Selection Sample Efficient for Reinforcement Learning?
by: Liu, Vincent, et al.
Published: (2023)

Energy-Guided Diffusion Sampling for Offline-to-Online Reinforcement Learning
by: Liu, Xu-Hui, et al.
Published: (2024)

Sample-Efficient Tabular Self-Play for Offline Robust Reinforcement Learning
by: Li, Na, et al.
Published: (2025)

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization
by: Liu, Zongkai, et al.
Published: (2024)

Sample Efficient Active Algorithms for Offline Reinforcement Learning
by: Roy, Soumyadeep, et al.
Published: (2026)

On Sample-Efficient Offline Reinforcement Learning: Data Diversity, Posterior Sampling, and Beyond
by: Nguyen-Tang, Thanh, et al.
Published: (2024)

Provable Domain Adaptation for Offline Reinforcement Learning with Limited Samples
by: Chen, Weiqin, et al.
Published: (2024)

Adaptive Scaling of Policy Constraints for Offline Reinforcement Learning
by: Jing, Tan, et al.
Published: (2025)

LEASE: Offline Preference-based Reinforcement Learning with High Sample Efficiency
by: Liu, Xiao-Yin, et al.
Published: (2024)

From Static Constraints to Dynamic Adaptation: Sample-Level Constraint Relaxation for Offline-to-Online Reinforcement Learning
by: Zu, Lipeng, et al.
Published: (2025)

Unifying Value Alignment and Assignment in Cross-Domain Offline Reinforcement Learning with Heterogeneous Datasets
by: Qiao, Zhongjian, et al.
Published: (2026)

Efficient Policy Evaluation with Safety Constraint for Reinforcement Learning
by: Chen, Claire, et al.
Published: (2024)

Multi-Agent Target Assignment and Path Finding for Intelligent Warehouse: A Cooperative Multi-Agent Deep Reinforcement Learning Perspective
by: Liu, Qi, et al.
Published: (2024)

Policy Constraint by Only Support Constraint for Offline Reinforcement Learning
by: Gao, Yunkai, et al.
Published: (2025)

Sample-Mean Anchored Thompson Sampling for Offline-to-Online Learning with Distribution Shift
by: Li, Bochao, et al.
Published: (2026)

Dual-Robust Cross-Domain Offline Reinforcement Learning Against Dynamics Shifts
by: Qiao, Zhongjian, et al.
Published: (2025)

Diffusion Policies with Offline and Inverse Reinforcement Learning for Promoting Physical Activity in Older Adults Using Wearable Sensors
by: Liu, Chang, et al.
Published: (2025)

Settling the Sample Complexity of Model-Based Offline Reinforcement Learning
by: Li, Gen, et al.
Published: (2022)

Automatic Constraint Policy Optimization based on Continuous Constraint Interpolation Framework for Offline Reinforcement Learning
by: Han, Xinchen, et al.
Published: (2026)

Cross-Domain Offline Policy Adaptation via Selective Transition Correction
by: Yan, Mengbei, et al.
Published: (2026)

Constraint-Adaptive Policy Switching for Offline Safe Reinforcement Learning
by: Chemingui, Yassine, et al.
Published: (2024)

Sample-Efficient Reinforcement Learning from Human Feedback via Information-Directed Sampling
by: Qi, Han, et al.
Published: (2025)

CS-GBA: A Critical Sample-based Gradient-guided Backdoor Attack for Offline Reinforcement Learning
by: Zhao, Yuanjie, et al.
Published: (2026)

Model-based Offline RL via Robust Value-Aware Model Learning with Implicitly Differentiable Adaptive Weighting
by: Qiao, Zhongjian, et al.
Published: (2026)

Offline Reinforcement Learning with Generative Trajectory Policies
by: Feng, Xinsong, et al.
Published: (2025)

Unleashing the Power of Pre-trained Language Models for Offline Reinforcement Learning
by: Shi, Ruizhe, et al.
Published: (2023)

On-Policy Policy Gradient Reinforcement Learning Without On-Policy Sampling
by: Corrado, Nicholas E., et al.
Published: (2023)

Diffusion-DICE: In-Sample Diffusion Guidance for Offline Reinforcement Learning
by: Mao, Liyuan, et al.
Published: (2024)

Offline Policy Evaluation for Reinforcement Learning with Adaptively Collected Data
by: Madhow, Sunil, et al.
Published: (2023)

Efficient Anti-exploration via VQVAE and Fuzzy Clustering in Offline Reinforcement Learning
by: Chen, Long, et al.
Published: (2026)

Deep Transfer $Q$-Learning for Offline Non-Stationary Reinforcement Learning
by: Chai, Jinhang, et al.
Published: (2025)

Stabilizing Policy Gradients for Sample-Efficient Reinforcement Learning in LLM Reasoning
by: Melo, Luckeciano C., et al.
Published: (2025)

Diffusion Policies for Risk-Averse Behavior Modeling in Offline Reinforcement Learning
by: Chen, Xiaocong, et al.
Published: (2024)

Distributionally Robust Model-Based Offline Reinforcement Learning with Near-Optimal Sample Complexity
by: Shi, Laixi, et al.
Published: (2022)

Succeed or Learn Slowly: Sample Efficient Off-Policy Reinforcement Learning for Mobile App Control
by: Papoudakis, Georgios, et al.
Published: (2025)

Relative Importance Sampling for off-Policy Actor-Critic in Deep Reinforcement Learning
by: Humayoo, Mahammad, et al.
Published: (2018)

Policy-Driven World Model Adaptation for Robust Offline Model-based Reinforcement Learning
by: Chen, Jiayu, et al.
Published: (2025)

Preferred-Action-Optimized Diffusion Policies for Offline Reinforcement Learning
by: Zhang, Tianle, et al.
Published: (2024)