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통찰 - Dynamic Anticipatory Mesh Optimization
DynAMO: Reinforcement Learning for Mesh Optimization in Hyperbolic Conservation Laws
The author introduces DynAMO, a reinforcement learning paradigm for Dynamic Anticipatory Mesh Optimization, aiming to improve mesh refinement strategies for hyperbolic conservation laws by anticipating future errors and optimizing long-term objectives.
DynAMO: Dynamic Anticipatory Mesh Optimization with Reinforcement Learning
Reinforcement learning for anticipatory mesh refinement improves accuracy and efficiency.
