Cover Image

Benchmarks for Reinforcement Learning with Biased Offline Data and Imperfect Simulators

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Linial, Ori, Tennenholtz, Guy, Shalit, Uri
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Structured Hybrid Mechanistic Models for Robust Estimation of Time-Dependent Intervention Outcomes
by: Meir, Tomer, et al.
Published: (2026)

Controllable User Simulation
by: Tennenholtz, Guy, et al.
Published: (2026)

Bayesian Regret Minimization in Offline Bandits
by: Petrik, Marek, et al.
Published: (2023)

Representation-Driven Reinforcement Learning
by: Nabati, Ofir, et al.
Published: (2023)

Heterogeneous Treatment Effect in Time-to-Event Outcomes: Harnessing Censored Data with Recursively Imputed Trees
by: Meir, Tomer, et al.
Published: (2025)

On the ERM Principle in Meta-Learning
by: Alon, Yannay, et al.
Published: (2024)

Set Valued Predictions For Robust Domain Generalization
by: Tsibulsky, Ron, et al.
Published: (2025)

Preference-based Conditional Treatment Effects and Policy Learning
by: Parnas, Dovid, et al.
Published: (2026)

CONFIDE: Contextual Finite Differences Modelling of PDEs
by: Linial, Ori, et al.
Published: (2023)

Malign Overfitting: Interpolation Can Provably Preclude Invariance
by: Wald, Yoav, et al.
Published: (2022)

Simulating Biases for Interpretable Fairness in Offline and Online Classifiers
by: Inácio, Ricardo, et al.
Published: (2025)

Contextual Online Pricing with (Biased) Offline Data
by: Zhang, Yixuan, et al.
Published: (2025)

DynaMITE-RL: A Dynamic Model for Improved Temporal Meta-Reinforcement Learning
by: Liang, Anthony, et al.
Published: (2024)

Aiming for Relevance
by: Porat, Bar Eini, et al.
Published: (2024)

Online Bandits with (Biased) Offline Data: Adaptive Learning under Distribution Mismatch
by: Cheung, Wang Chi, et al.
Published: (2024)

INSIGHTS: Demonstration-Based Summaries of Time Series Predictors
by: Porat, Bar Eini, et al.
Published: (2026)

Towards Regulatory-Confirmed Adaptive Clinical Trials: Machine Learning Opportunities and Solutions
by: Klein, Omer Noy, et al.
Published: (2025)

Temporal Abstraction in Reinforcement Learning with Offline Data
by: Ayyagari, Ranga Shaarad, et al.
Published: (2024)

Offline Reinforcement Learning with Domain-Unlabeled Data
by: Nishimori, Soichiro, et al.
Published: (2024)

A Continual Offline Reinforcement Learning Benchmark for Navigation Tasks
by: Kobanda, Anthony, et al.
Published: (2025)

Benchmarking Offline Multi-Objective Reinforcement Learning in Critical Care
by: Bansal, Aryaman, et al.
Published: (2025)

OffSim: Offline Simulator for Model-based Offline Inverse Reinforcement Learning
by: Ahn, Woo-Jin, et al.
Published: (2025)

Improving Offline Reinforcement Learning with Inaccurate Simulators
by: Hou, Yiwen, et al.
Published: (2024)

Set-Valued Policy Learning
by: Fuentes-Vicente, Laura, et al.
Published: (2026)

Spectral Bellman Method: Unifying Representation and Exploration in RL
by: Nabati, Ofir, et al.
Published: (2025)

A Benchmark Environment for Offline Reinforcement Learning in Racing Games
by: Macaluso, Girolamo, et al.
Published: (2024)

A Real-World Quadrupedal Locomotion Benchmark for Offline Reinforcement Learning
by: Zhang, Hongyin, et al.
Published: (2023)

Trajectory-Level Data Augmentation for Offline Reinforcement Learning
by: Schmähling, Tobias, et al.
Published: (2026)

Best Arm Identification with Possibly Biased Offline Data
by: Yang, Le, et al.
Published: (2025)

Guided Data Augmentation for Offline Reinforcement Learning and Imitation Learning
by: Corrado, Nicholas E., et al.
Published: (2023)

Active Advantage-Aligned Online Reinforcement Learning with Offline Data
by: Liu, Xuefeng, et al.
Published: (2025)

Offline Constrained Reinforcement Learning under Partial Data Coverage
by: Ko, Seokmin, et al.
Published: (2025)

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies
by: Gutman, Rom, et al.
Published: (2025)

Is merging worth it? Securely evaluating the information gain for causal dataset acquisition
by: Fawkes, Jake, et al.
Published: (2024)

Data-Incremental Continual Offline Reinforcement Learning
by: Gai, Sibo, et al.
Published: (2024)

Flexible Blood Glucose Control: Offline Reinforcement Learning from Human Feedback
by: Emerson, Harry, et al.
Published: (2025)

Offline Trajectory Optimization for Offline Reinforcement Learning
by: Zhao, Ziqi, et al.
Published: (2024)

Enhancing Online Reinforcement Learning with Meta-Learned Objective from Offline Data
by: Deng, Shilong, et al.
Published: (2025)

Optimal Perturbation Budget Allocation for Data Poisoning in Offline Reinforcement Learning
by: Qiu, Junnan, et al.
Published: (2025)

Equivariant Offline Reinforcement Learning
by: Tangri, Arsh, et al.
Published: (2024)