Uncertainty-Aware Selection of Online Algorithms with Simulator Ensembles

arXiv:2609.32170 · cs.LG, cs.AI · Submitted 2026-09-26 · Read on arXiv

cs.LG, cs.AI

Submitted: 2026-09-26

Updated: 2026-09-26

Terminology

• Regret — 87× in this paper · explained in 3 episodes
• Reinforcement Learning — 21× in this paper · explained in 4 episodes
• Thompson Sampling — 17× in this paper
• Regularization — 7× in this paper · explained in 3 episodes
• Robustness — 6× in this paper · explained in 5 episodes
• System Identification — 6× in this paper · explained in 3 episodes
• World Model — 6× in this paper · explained in 7 episodes
• Sim-to-Real Transfer — 5× in this paper · explained in 2 episodes
• Digital Twin — 4× in this paper · explained in 5 episodes
• In International Conference on Learning Representations — 4× in this paper
• International Conference on Machine Learning — 4× in this paper
• Reward Shaping — 4× in this paper · explained in 2 episodes
• Adam — 3× in this paper · explained in 2 episodes
• Bayesian Optimization — 3× in this paper · explained in 3 episodes
• Deep Reinforcement Learning — 3× in this paper · explained in 2 episodes
• Epistemic Uncertainty — 3× in this paper · explained in 10 episodes
• Online Reinforcement Learning — 3× in this paper · explained in 2 episodes
• Action Space — 2× in this paper · explained in 1 episode
• Calibration — 2× in this paper · explained in 7 episodes
• Distribution Shift — 2× in this paper · explained in 5 episodes
• IEEE International Conference on Robotics and Automation — 2× in this paper
• Objective Function — 2× in this paper · explained in 2 episodes
• Plug-In and Uncertainty-Aware — 2× in this paper
• Q-learning — 2× in this paper · explained in 3 episodes
• Sim-to-Real Gap — 2× in this paper · explained in 6 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Optimal Transport — 1× in this paper · explained in 5 episodes
• Reinforcement Learning (RL) — 1× in this paper · explained in 25 episodes
• Sample Efficiency — 1× in this paper · explained in 4 episodes
• Trace — 1× in this paper · explained in 2 episodes

Sources

• Challenges of Real-World Reinforcement Learning
• The Typical Behavior of Bandit Algorithms
• Uncertainty-Aware Robotic World Model Makes Offline Model-Based Reinforcement Learning Work on Real Robots
• Proximal Policy Optimization Algorithms
• Distributionally Robust Reinforcement Learning
• Towards Data-Driven Offline Simulations for Online Reinforcement Learning
• Oralytics Reinforcement Learning Algorithm
• Automatic Reward Shaping from Multi-Objective Human Heuristics
• A Diffusion-Model Subpopulation Digital Twin for Mobile Health Deployment: A Case Study on the HeartSteps Intervention
• Foundation Models for Decision Making: Problems, Methods, and Opportunities

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