Offline Reinforcement Learning
130 papers
Papers per year
1
4
3
15
29
24
26
25
3
'20
'25
Papers
The Generalization Gap in Offline Reinforcement Learning
ICLR 2024
Towards an Information Theoretic Framework of Context-Based Offline Meta-Reinforcement Learning
NeurIPS 2024
Uni-O4: Unifying Online and Offline Deep Reinforcement Learning with Multi-Step On-Policy Optimization
ICLR 2024
Worst-Case Offline Reinforcement Learning with Arbitrary Data Support
NeurIPS 2024
Confidence-Conditioned Value Functions for Offline Reinforcement Learning
ICLR 2023
Corruption-Robust Offline Reinforcement Learning with General Function Approximation
NeurIPS 2023
Extreme Q-Learning: MaxEnt RL without Entropy
ICLR 2023
Goal-Conditioned Predictive Coding for Offline Reinforcement Learning
NeurIPS 2023
Harnessing Mixed Offline Reinforcement Learning Datasets via Trajectory Weighting
ICLR 2023
HIQL: Offline Goal-Conditioned RL with Latent States as Actions
NeurIPS 2023
Hokoff: Real Game Dataset from Honor of Kings and its Offline Reinforcement Learning Benchmarks
NeurIPS 2023
Importance Weighted Actor-Critic for Optimal Conservative Offline Reinforcement Learning
NeurIPS 2023
In-sample Actor Critic for Offline Reinforcement Learning
ICLR 2023
Offline Congestion Games: How Feedback Type Affects Data Coverage Requirement
ICLR 2023
Offline RL with No OOD Actions: In-Sample Learning via Implicit Value Regularization
ICLR 2023
Policy-Adaptive Estimator Selection for Off-Policy Evaluation
AAAI 2023
Policy Expansion for Bridging Offline-to-Online Reinforcement Learning
ICLR 2023
Recovering from Out-of-sample States via Inverse Dynamics in Offline Reinforcement Learning
NeurIPS 2023
ReDS: Offline RL With Heteroskedastic Datasets via Support Constraints
NeurIPS 2023
Reining Generalization in Offline Reinforcement Learning via Representation Distinction
NeurIPS 2023
Safe Policy Improvement for POMDPs via Finite-State Controllers
AAAI 2023
Supported Value Regularization for Offline Reinforcement Learning
NeurIPS 2023
The In-Sample Softmax for Offline Reinforcement Learning
ICLR 2023
The Provable Benefit of Unsupervised Data Sharing for Offline Reinforcement Learning
ICLR 2023
Train Once, Get a Family: State-Adaptive Balances for Offline-to-Online Reinforcement Learning
NeurIPS 2023