AI RESEARCH
Autonomous Adaptive Solver Selection for Chemistry Integration via Reinforcement Learning
arXiv CS.LG
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ArXi:2604.00264v1 Announce Type: new The computational cost of stiff chemical kinetics remains a dominant bottleneck in reacting-flow simulation, yet hybrid integration strategies are typically driven by hand-tuned heuristics or supervised predictors that make myopic decisions from instantaneous local state. We