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#reinforcement learning Open access Sep 2026

Self-Configuring Hierarchies with Meta-Adaptive Hierarchical Reinforcement Learning for Multi-Agent cooperative Control

Solves the rigidity of manual hyperparameter tuning in traffic control using Meta-MOHRL, a self-configuring HRL framework for optimizing unpredictable multi-objective traffic flows. A PyTorch framework enabling multi-objective traffic coordination. Includes SUMO environment & topologies, and SoTA hierarchical baselines...

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