Real-Time Holding Control for Transfer Synchronization via Robust Multiagent Reinforcement Learning

This study presents a robust deep reinforcement learning (RL) approach for real-time, network-wide holding control with transfer synchronization, considering stochastic passenger demand and vehicle running time during daily operations. The problem is formulated within a multi-agent RL framework wher...

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