A single-agent deep Q-learning model with MSA guidance sequentially assigns routes and approximates system-optimal traffic assignment on the Braess and OW networks within 0.35%.
Multi-agent deep reinforce- ment learning for large-scale traffic signal control,
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Reinforcement Learning-based Sequential Route Recommendation for System-Optimal Traffic Assignment
A single-agent deep Q-learning model with MSA guidance sequentially assigns routes and approximates system-optimal traffic assignment on the Braess and OW networks within 0.35%.