A two-level reduction framework (clustering plus POD) makes optimal consensus control of large-scale agent-based models computationally tractable, with numerical speed-ups exceeding 100 in opinion dynamics tests.
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Hierarchical clustering and dimensional reduction for optimal control of large-scale agent-based models
A two-level reduction framework (clustering plus POD) makes optimal consensus control of large-scale agent-based models computationally tractable, with numerical speed-ups exceeding 100 in opinion dynamics tests.