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Offline Reinforcement Learning
84 directly classified papers
Papers per year
2019: 4
2020: 2
2021: 11
2022: 23
2023: 15
2024: 18
2025: 11
Papers
Cross-Validated Off-Policy Evaluation
AAAI 2025
Markov Balance Satisfaction Improves Performance in Strictly Batch Offline Imitation Learning
AAAI 2025
In-Dataset Trajectory Return Regularization for Offline Preference-based Reinforcement Learning
AAAI 2025
Offline Safe Reinforcement Learning Using Trajectory Classification
AAAI 2025
Are Expressive Models Truly Necessary for Offline RL?
AAAI 2025
Cooperative Policy Agreement: Learning Diverse Policy for Offline MARL
AAAI 2025
Improving Generalization in Offline Reinforcement Learning via Latent Distribution Representation Learning
AAAI 2025
Dynamic Uncertainty Estimation for Offline Reinforcement Learning
AAAI 2025
Beyond Online Sampling: Bridging Offline-to-Online Alignment via Dynamic Data Transformation for LLMs
EMNLP 2025
MGDA: Model-based Goal Data Augmentation for Offline Goal-conditioned Weighted Supervised Learning
AAAI 2025
Constraint-Adaptive Policy Switching for Offline Safe Reinforcement Learning
AAAI 2025
Exploiting Action Impact Regularity and Exogenous State Variables for Offline Reinforcement Learning (Abstract Reprint)
AAAI 2024
The Edge-of-Reach Problem in Offline Model-Based Reinforcement Learning
NIPS 2024
Worst-Case Offline Reinforcement Learning with Arbitrary Data Support
NIPS 2024
DMC-VB: A Benchmark for Representation Learning for Control with Visual Distractors
NIPS 2024
Robustly Improving Bandit Algorithms with Confounded and Selection Biased Offline Data: A Causal Approach
AAAI 2024
Doubly Mild Generalization for Offline Reinforcement Learning
NIPS 2024
Towards an Information Theoretic Framework of Context-Based Offline Meta-Reinforcement Learning
NIPS 2024
MetaReflection: Learning Instructions for Language Agents using Past Reflections
EMNLP 2024
Multi-Agent Domain Calibration with a Handful of Offline Data
NIPS 2024
Scaling Offline Evaluation of Reinforcement Learning Agents through Abstraction
AAAI 2024
Reinforcement Learning Gradients as Vitamin for Online Finetuning Decision Transformers
NIPS 2024
Sample Complexity Reduction via Policy Difference Estimation in Tabular Reinforcement Learning
NIPS 2024
Decision Mamba: A Multi-Grained State Space Model with Self-Evolution Regularization for Offline RL
NIPS 2024
Logarithmic Smoothing for Pessimistic Off-Policy Evaluation, Selection and Learning
NIPS 2024
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