Qili Shen

On the Computational Limits of AI4S-RL : A Unified $\varepsilon$-$N$ Analysis

Recent work increasingly adopts AI for Science (AI4S) models to replace expensive PDE solvers as simulation environments for reinforcement learning (RL), enabling faster training in complex physical control tasks. However, using approximate simulators introduces modeling errors that affect the learn…