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Deep Reinforcement Learning for Adaptive Mesh Refinement: A Training Parameter Study
Adaptive mesh refinement (AMR) enables efficient solution of partial differential equations by dynamically allocating computational resources to regions requiring higher resolution. It has been demonstrated that deep reinforcement learning agents could learn effective mesh adaptation policies. Howev
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