Deep Reinforcement Learning for Ride-sharing Dispatching and Repositioning

被引：0
|
作者：
Qin, Zhiwei [1 ,2 ]
Tang, Xiaocheng [1 ,2 ]
Jiao, Yan [1 ,2 ]
Zhang, Fan [2 ]
Wang, Chenxi [1 ,3 ]
Li, Qun [3 ]
机构：
[1] DiDi Res Amer, Mountain View, CA 94043 USA
[2] DiDi AI Labs, Beijing, Peoples R China
[3] DiDi Res, Beijing, Peoples R China
来源：
PROCEEDINGS OF THE TWENTY-EIGHTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE | 2019年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this demo, we will present a simulation-based human-computer interaction of deep reinforcement learning in action on order dispatching and driver repositioning for ride-sharing. Specifically, we will demonstrate through several specially designed domains how we use deep reinforcement learning to train agents (drivers) to have longer optimization horizon and to cooperate to achieve higher objective values collectively.
引用
收藏
页码：6566 / 6568
页数：3
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