Titlebook: Reinforcement Learning in the Ridesharing Marketplace; Zhiwei (Tony) Qin,Xiaocheng Tang,Jieping Ye Book 2025 The Editor(s) (if applicable)

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Routing,isions on a road network, typically with output of matching and repositioning algorithms as input. This is not to be confused with the ., which is a separate class of macro-level problems that we elaborate in Sect.?7.2.

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Related Methods,le by treating the task of learning the action values .(.,?.) in RL as estimating the long-term counter-factual effects of applying the different actions to a given current state, to which knowing the corresponding causal structure in the environment is highly helpful.

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Closing Remarks,, but as we have seen from the current literature, challenges remain in tackling complexity in the learning algorithms, the coordination among the agents, and the joint optimization of multiple levers. Along tackling these challenges, we expect that domain knowledge in ridesharing as well as transpo

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