Multi-agent RL tunes parameters of decentralized state-feedback traffic controllers, matching single-agent performance with better resilience to failures and disturbances in simulation.
Integrated traffic control for freeway recurrent bottleneck based on deep reinforcement learning,
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Adaptive Tuning of Parameterized Traffic Controllers via Multi-Agent Reinforcement Learning
Multi-agent RL tunes parameters of decentralized state-feedback traffic controllers, matching single-agent performance with better resilience to failures and disturbances in simulation.