Robust Reinforcement Learning Strategies with Evolving Curriculum for Efficient Bus Operations in Smart Cities
Public transit systems are critical to the quality of urban life, and enhancing their efficiency is essential for building cost-effective and sustainable smart cities. Historically, researchers sought reinforcement learning (RL) applications to mitigate bus bunching issues with holding strategies. N...
Main Authors: | , , , , , , , , |
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Format: | Article |
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Multidisciplinary Digital Publishing Institute
2025
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Online Access: | https://hdl.handle.net/1721.1/157936 |