most citedMulti-Agent Reinforcement Learning for Order-dispatching via Order-Vehicle Distribution Matching

80 citations · 87 across the 4 of their papers we have counts for

collaborators

6 papers

cs.LG20211 cited

A Deep Value-network Based Approach for Multi-Driver Order Dispatching

Xiaocheng Tang, Zhiwei Qin, Fan Zhang +5

Recent works on ride-sharing order dispatching have highlighted the importance of taking into account both the spatial and temporal dynamics in the dispatching process for improvin…

cs.MA201980 cited

Multi-Agent Reinforcement Learning for Order-dispatching via Order-Vehicle Distribution Matching

Ming Zhou, Jiarui Jin, Weinan Zhang +6

Improving the efficiency of dispatching orders to vehicles is a research hotspot in online ride-hailing systems. Most of the existing solutions for order-dispatching are centralize…

cs.LG2019

Similarity Kernel and Clustering via Random Projection Forests

Donghui Yan, Songxiang Gu, Ying Xu +1

Similarity plays a fundamental role in many areas, including data mining, machine learning, statistics and various applied domains. Inspired by the success of ensemble methods and…

cs.LG20193 cited

Environment Reconstruction with Hidden Confounders for Reinforcement Learning based Recommendation

Wenjie Shang, Yang Yu, Qingyang Li +3

Reinforcement learning aims at searching the best policy model for decision making, and has been shown powerful for sequential recommendations. The training of the policy by reinfo…

cs.MA2019

CoRide: Joint Order Dispatching and Fleet Management for Multi-Scale Ride-Hailing Platforms

Jiarui Jin, Ming Zhou, Weinan Zhang +9

How to optimally dispatch orders to vehicles and how to tradeoff between immediate and future returns are fundamental questions for a typical ride-hailing platform. We model ride-h…

cs.MA20193 cited

Efficient Ridesharing Order Dispatching with Mean Field Multi-Agent Reinforcement Learning

Minne Li, Zhiwei, Qin +7

A fundamental question in any peer-to-peer ridesharing system is how to, both effectively and efficiently, dispatch user's ride requests to the right driver in real time. Tradition…