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Single-agent Reinforcement Learning Model for Regional Adaptive Traffic Signal Control

arXiv — cs.LG•Tuesday, November 4, 2025 at 5:00:00 AM
PositiveArtificial Intelligence

Single-agent Reinforcement Learning Model for Regional Adaptive Traffic Signal Control

A new study highlights the potential of a single-agent reinforcement learning model for regional adaptive traffic signal control, addressing scalability issues faced by multi-agent frameworks. This approach could significantly improve traffic management, leading to smoother commutes and reduced congestion. As cities grow and traffic patterns become more complex, innovative solutions like this are crucial for enhancing urban mobility and efficiency.
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