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Offline Reinforcement Learning

84 directly classified papers

Papers per year

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