Co-DQL, a combination of double Q-learning, UCB exploration, mean field modeling, and local reward/state sharing, reduces simulated traffic delays relative to several MARL baselines.
Traffic network micro-simulation model and control algorithm based on approximate dynamic program- ming,
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Large-Scale Traffic Signal Control Using a Novel Multi-Agent Reinforcement Learning
Co-DQL, a combination of double Q-learning, UCB exploration, mean field modeling, and local reward/state sharing, reduces simulated traffic delays relative to several MARL baselines.