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cs.LG2026
Evolving Robustness--Exploration Trade-off in Online Reinforcement Learning via Quantile Bayesian Risk MDPs
Meichen Song, Yuhao Wang, Enlu Zhou
In online reinforcement learning, data scarcity creates epistemic uncertainty that makes robustness important early in learning, whereas sufficient exploration is needed to learn t…
cs.LG2026
Optimal Data Acquisition for Reinforcement Learning: A Large Deviations Perspective
Mingjie Hu, Jian-Qiang Hu, Enlu Zhou
Data acquisition efficiency is a central challenge in deploying reinforcement learning in business and healthcare operations, where interactions are costly, slow, and often involve…
cs.LG2026
Adaptive Simulation Experiment for LLM Policy Optimization
Mingjie Hu, Siyang Gao, Jian-qiang Hu +1
Large language models (LLMs) have significant potential to improve operational efficiency in operations management. Deploying these models requires specifying a policy that governs…