2025 Poster "offline reinforcement learning" Papers
30 papers found
$q$-exponential family for policy optimization
Lingwei Zhu, Haseeb Shah, Han Wang et al.
Adaptable Safe Policy Learning from Multi-task Data with Constraint Prioritized Decision Transformer
Ruiqi Xue, Ziqian Zhang, Lihe Li et al.
ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning
Zeyuan Liu, Zhihe Yang, Jiawei Xu et al.
Adversarial Policy Optimization for Offline Preference-based Reinforcement Learning
Hyungkyu Kang, Min-hwan Oh
DoF: A Diffusion Factorization Framework for Offline Multi-Agent Reinforcement Learning
Chao Li, Ziwei Deng, Chenxing Lin et al.
Efficient Online Reinforcement Learning Fine-Tuning Need Not Retain Offline Data
Zhiyuan Zhou, Andy Peng, Qiyang Li et al.
Energy-Weighted Flow Matching for Offline Reinforcement Learning
Shiyuan Zhang, Weitong Zhang, Quanquan Gu
Fat-to-Thin Policy Optimization: Offline Reinforcement Learning with Sparse Policies
Lingwei Zhu, Han Wang, Yukie Nagai
Fewer May Be Better: Enhancing Offline Reinforcement Learning with Reduced Dataset
Yiqin Yang, Quanwei Wang, Chenghao Li et al.
Finite-Time Bounds for Average-Reward Fitted Q-Iteration
Jongmin Lee, Ernest Ryu
FOSP: Fine-tuning Offline Safe Policy through World Models
Chenyang Cao, Yucheng Xin, Silang Wu et al.
Learning from Reward-Free Offline Data: A Case for Planning with Latent Dynamics Models
Uladzislau Sobal, Wancong Zhang, Kyunghyun Cho et al.
Learning on One Mode: Addressing Multi-modality in Offline Reinforcement Learning
Mianchu Wang, Yue Jin, Giovanni Montana
Learning Preferences without Interaction for Cooperative AI: A Hybrid Offline-Online Approach
Haitong Ma, Haoran Yu, Haobo Fu et al.
Mitigating Reward Over-optimization in Direct Alignment Algorithms with Importance Sampling
Nguyen Phuc, Ngoc-Hieu Nguyen, Duy M. H. Nguyen et al.
Model-Free Offline Reinforcement Learning with Enhanced Robustness
Chi Zhang, Zain Ulabedeen Farhat, George Atia et al.
Model Selection for Off-policy Evaluation: New Algorithms and Experimental Protocol
Pai Liu, Lingfeng Zhao, Shivangi Agarwal et al.
MOSDT: Self-Distillation-Based Decision Transformer for Multi-Agent Offline Safe Reinforcement Learning
Yuchen Xia, Yunjian Xu
Neural Stochastic Differential Equations for Uncertainty-Aware Offline RL
Cevahir Koprulu, Franck Djeumou, ufuk topcu
Offline RL by Reward-Weighted Fine-Tuning for Conversation Optimization
Subhojyoti Mukherjee, Viet Lai, Raghavendra Addanki et al.
Offline RL in Regular Decision Processes: Sample Efficiency via Language Metrics
Ahana Deb, Roberto Cipollone, Anders Jonsson et al.
OGBench: Benchmarking Offline Goal-Conditioned RL
Seohong Park, Kevin Frans, Benjamin Eysenbach et al.
Pretraining a Shared Q-Network for Data-Efficient Offline Reinforcement Learning
Jongchan Park, Mingyu Park, Donghwan Lee
REINFORCEMENT LEARNING FOR INDIVIDUAL OPTIMAL POLICY FROM HETEROGENEOUS DATA
Rui Miao, Babak Shahbaba, Annie Qu
RLZero: Direct Policy Inference from Language Without In-Domain Supervision
Harshit Sushil Sikchi, Siddhant Agarwal, Pranaya Jajoo et al.
RTDiff: Reverse Trajectory Synthesis via Diffusion for Offline Reinforcement Learning
Qianlan Yang, Yu-Xiong Wang
Scrutinize What We Ignore: Reining In Task Representation Shift Of Context-Based Offline Meta Reinforcement Learning
Hai Zhang, Boyuan Zheng, Tianying Ji et al.
Value-aligned Behavior Cloning for Offline Reinforcement Learning via Bi-level Optimization
Xingyu Jiang, Ning Gao, Xiuhui Zhang et al.
Value-Guided Decision Transformer: A Unified Reinforcement Learning Framework for Online and Offline Settings
Hongling Zheng, Li Shen, Yong Luo et al.
What Makes a Good Diffusion Planner for Decision Making?
Haofei Lu, Dongqi Han, Yifei Shen et al.