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Peer Review #2 of "Sharing diverse information gets driver agents to learn faster: an application in en route trip building (v0.1)"
With the increase in the use of private transportation, developing more efficient ways to distribute routes in a traffic network has become more and more important. Several attempts to address this issue have already been proposed, either by using a central authority to assign routes to the vehicles, or by means of a learning process where drivers select their best routes based on their previous experiences. The present work addresses a way to connect reinforcement learning to new technologiesdoi:10.7287/peerj-cs.428v0.1/reviews/2 fatcat:xtyo3qhdg5aqlb6jvcc2wjyvde