Cover Image

Enhancing Offline Model-Based RL via Active Model Selection: A Bayesian Optimization Perspective

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yang, Yu-Wei, Chan, Yun-Ming, Hung, Wei, Liu, Xi, Hsieh, Ping-Chun
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

Q-Pensieve: Boosting Sample Efficiency of Multi-Objective RL Through Memory Sharing of Q-Snapshots
by: Hung, Wei, et al.
Published: (2022)

BOFormer: Learning to Solve Multi-Objective Bayesian Optimization via Non-Markovian RL
by: Hung, Yu-Heng, et al.
Published: (2025)

On the Learnability of Offline Model-Based Optimization: A Ranking Perspective
by: Lyu, Shen-Huan, et al.
Published: (2026)

Offline Imitation of Badminton Player Behavior via Experiential Contexts and Brownian Motion
by: Wang, Kuang-Da, et al.
Published: (2024)

Cross-Domain Policy Optimization via Bellman Consistency and Hybrid Critics
by: Chen, Ming-Hong, et al.
Published: (2026)

Scaling Offline Model-Based RL via Jointly-Optimized World-Action Model Pretraining
by: Cheng, Jie, et al.
Published: (2024)

Efficient Action-Constrained Reinforcement Learning via Acceptance-Rejection Method and Augmented MDPs
by: Hung, Wei, et al.
Published: (2025)

Offline Model-Based Optimization: Comprehensive Review
by: Kim, Minsu, et al.
Published: (2025)

From Reward-Free Representations to Preferences: Rethinking Offline Preference-Based Reinforcement Learning
by: Yang, Jun-Jie, et al.
Published: (2026)

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

Non-Stationary Restless Multi-Armed Bandits with Provable Guarantee
by: Hung, Yu-Heng, et al.
Published: (2025)

Diffusion Models as Optimizers for Efficient Planning in Offline RL
by: Huang, Renming, et al.
Published: (2024)

Making Offline RL Online: Collaborative World Models for Offline Visual Reinforcement Learning
by: Wang, Qi, et al.
Published: (2023)

Inference Time Policy Optimization for Offline RL with Differentiable World Models
by: Deb, Rohan, et al.
Published: (2026)

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

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

Reinformer: Max-Return Sequence Modeling for Offline RL
by: Zhuang, Zifeng, et al.
Published: (2024)

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

Learning to Trust Bellman Updates: Selective State-Adaptive Regularization for Offline RL
by: Luo, Qin-Wen, et al.
Published: (2025)

Learning Human-Like RL Agents Through Trajectory Optimization With Action Quantization
by: Guo, Jian-Ting, et al.
Published: (2025)

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

A Reward-Free Viewpoint on Multi-Objective Reinforcement Learning
by: Chen, Ying-Tu, et al.
Published: (2026)

Guided Trajectory Generation with Diffusion Models for Offline Model-based Optimization
by: Yun, Taeyoung, et al.
Published: (2024)

A Bayesian Model Selection Criterion for Selecting Pretraining Checkpoints
by: Munn, Michael, et al.
Published: (2024)

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

Synthesizing Programmatic Reinforcement Learning Policies with Large Language Model Guided Search
by: Liu, Max, et al.
Published: (2024)

Offline Model-Based Optimization by Learning to Rank
by: Tan, Rong-Xi, et al.
Published: (2024)

Active Advantage-Aligned Online Reinforcement Learning with Offline Data
by: Liu, Xuefeng, et al.
Published: (2025)

Solving Continual Offline RL through Selective Weights Activation on Aligned Spaces
by: Hu, Jifeng, et al.
Published: (2024)

Decision MetaMamba: Enhancing Selective SSM in Offline RL with Heterogeneous Sequence Mixing
by: Kim, Wall, et al.
Published: (2026)

Decision MetaMamba: Enhancing Selective SSM in Offline RL with Heterogeneous Sequence Mixing
by: Kim, Wall, et al.
Published: (2024)

AdamO: A Collapse-Suppressed Optimizer for Offline RL
by: Qiao, Nan, et al.
Published: (2026)

Fat-to-Thin Policy Optimization: Offline RL with Sparse Policies
by: Zhu, Lingwei, et al.
Published: (2025)

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

Scaling Offline RL via Efficient and Expressive Shortcut Models
by: Espinosa-Dice, Nicolas, et al.
Published: (2025)

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

Offline RL via Feature-Occupancy Gradient Ascent
by: Neu, Gergely, et al.
Published: (2024)

Mitigating Distribution Shift in Model-based Offline RL via Shifts-aware Reward Learning
by: Luo, Wang, et al.
Published: (2024)

Towards Universal Offline Black-Box Optimization via Learning Language Model Embeddings
by: Tan, Rong-Xi, et al.
Published: (2025)

Meta-DT: Offline Meta-RL as Conditional Sequence Modeling with World Model Disentanglement
by: Wang, Zhi, et al.
Published: (2024)