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University of Waterloo, Kasaiezadeh is with General Motors Company
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This research proposes a novel practical hybrid control scheme - learning agent-based MPC (LAMPC), combining the model-based AMPC approach and data-based learning methods to improve the holistic vehicle performance for multi-agent systems.
Weighted maximization can unlock better navigation plans, but until now, it was too slow to use in practice.