
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.


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dynamo-reinforcement-learning-for-mesh-optimization-in-hyperbolic-conservation-laws


DynAMO: Reinforcement Learning for Mesh Optimization in Hyperbolic Conservation Laws


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Reinforcement learning for anticipatory mesh refinement improves accuracy and efficiency.


dynamo-dynamic-anticipatory-mesh-optimization-with-reinforcement-learning


DynAMO: Dynamic Anticipatory Mesh Optimization with Reinforcement Learning
