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Offline RL

Papers

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Showing 726–750 of 755 papers

TitleStatusHype
Offline RL Policies Should be Trained to be Adaptive—0
Offline RL via Feature-Occupancy Gradient Ascent—0
Offline RL with Observation Histories: Analyzing and Improving Sample Complexity—0
Offline RL With Realistic Datasets: Heteroskedasticity and Support Constraints—0
Offline Robotic World Model: Learning Robotic Policies without a Physics Simulator—0
Offline Trajectory Generalization for Offline Reinforcement Learning—0
OffRIPP: Offline RL-based Informative Path Planning—0
OmniRL: In-Context Reinforcement Learning by Large-Scale Meta-Training in Randomized Worlds—0
Sample Complexity of Offline Reinforcement Learning with Deep ReLU Networks—0
On Instance-Dependent Bounds for Offline Reinforcement Learning with Linear Function Approximation—0
On Multi-objective Policy Optimization as a Tool for Reinforcement Learning: Case Studies in Offline RL and Finetuning—0
On Sample-Efficient Offline Reinforcement Learning: Data Diversity, Posterior Sampling, and Beyond—0
On the Role of Discount Factor in Offline Reinforcement Learning—0
On the Sample Complexity of Vanilla Model-Based Offline Reinforcement Learning with Dependent Samples—0
On the Statistical Complexity for Offline and Low-Adaptive Reinforcement Learning with Structures—0
Offline Preference-Based Apprenticeship Learning—0
OPAL: Offline Primitive Discovery for Accelerating Offline Reinforcement Learning—0
OPERA: Automatic Offline Policy Evaluation with Re-weighted Aggregates of Multiple Estimators—0
Optimal Conservative Offline RL with General Function Approximation via Augmented Lagrangian—0
Binary Reward Labeling: Bridging Offline Preference and Reward-Based Reinforcement Learning—0
Optimal Single-Policy Sample Complexity and Transient Coverage for Average-Reward Offline RL—0
Optimistic Model Rollouts for Pessimistic Offline Policy Optimization—0
Optimization Solution Functions as Deterministic Policies for Offline Reinforcement Learning—0
Optimizing Trajectories for Highway Driving with Offline Reinforcement Learning—0
Oracle Inequalities for Model Selection in Offline Reinforcement Learning—0
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All datasetsD4RLWalker2d

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1KFCAverage Reward81.8—Unverified
2ADMPOAverage Reward81—Unverified
3Decision Transformer (DT)Average Reward73.5—Unverified
#ModelMetricClaimedVerifiedStatus
1ParPID4RL Normalized Score151.4—Unverified