Zhaoxing Yang

Orcid: 0000-0002-7008-7629

According to our database1, Zhaoxing Yang authored at least 13 papers between 2021 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Optimizing Long-Term Efficiency and Fairness in Ride-Hailing Under Budget Constraint via Joint Order Dispatching and Driver Repositioning.
IEEE Trans. Knowl. Data Eng., July, 2024

Rethinking Order Dispatching in Online Ride-Hailing Platforms.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Risk-Aware Constrained Reinforcement Learning with Non-Stationary Policies.
Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024

2023
Multi-Intersection Management for Connected Autonomous Vehicles by Reinforcement Learning.
Proceedings of the 43rd IEEE International Conference on Distributed Computing Systems, 2023

User-Oriented Robust Reinforcement Learning.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

DeCOM: Decomposed Policy for Constrained Cooperative Multi-Agent Reinforcement Learning.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Joint Charging and Relocation Recommendation for E-Taxi Drivers via Multi-Agent Mean Field Hierarchical Reinforcement Learning.
IEEE Trans. Mob. Comput., 2022

Enabling Optimal Control Under Demand Elasticity for Electric Vehicle Charging Systems.
IEEE Trans. Mob. Comput., 2022

User-Oriented Robust Reinforcement Learning.
CoRR, 2022

Optimizing Long-Term Efficiency and Fairness in Ride-Hailing via Joint Order Dispatching and Driver Repositioning.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

2021
DeCOM: Decomposed Policy for Constrained Cooperative Multi-Agent Reinforcement Learning.
CoRR, 2021

Multi-Agent Reinforcement Learning for Urban Crowd Sensing with For-Hire Vehicles.
Proceedings of the 40th IEEE Conference on Computer Communications, 2021

Constrained Multi-Agent Reinforcement Learning for Managing Electric Self-Driving Taxis.
Proceedings of the 27th IEEE International Conference on Parallel and Distributed Systems, 2021


  Loading...