Feudal Latent Space Exploration for Coordinated Multi-agent Reinforcement Learning
Xiangyu Liu, Ying Tan.In IEEE Transactions on Neural Networks and Learning Systems (TNNLS, IF=10.451) 2022. [Download paper]
Xiangyu Liu Homepage
About me
I received my PhD degree in July 2020, under the supervision of Prof. Ying Tan at the Key Laboratory of machine perception and intelligence, School of Electronics Engineering and Computer Science, Peking University (EECS, PKU).
I received my B.S. of Intelligence Science and Technology in Nankai University and a dual degree of Business Administration from the Tianjin University in 2015.
Contact information
Email: liuxiangyu.george@gmail.com
Wechat: shawnlue_lxy93
Research Interests
My research focuses on machine learning and applications. In particular, I am working on Reinforcement Learning, Mechansim Design, Game Theory, Evolutionary Computation and their applications, e.g., mechanism design in e-commerce advertising and game AI.
Nothing is more practical than a good theory.
Publications
In IEEE Transactions on Neural Networks and Learning Systems (TNNLS, IF=10.451) 2022. [Download paper]On Designing a Two-stage Auction for Online Advertising
Yiqing Wang, Xiangyu Liu, Zhenzhe Zheng, Zhilin Zhang, Miao Xu, Chuan Yu, Fan Wu.
In WWW 2022. [Download paper]A Cooperative-Competitive Multi-Agent Framework for Auto-bidding in Online Advertising
Chao Wen, Miao Xu, Zhilin Zhang, Zhenzhe Zheng, Yuhui Wang, Xiangyu Liu, Yu Rong, Dong Xie, Xiaoyang Tan, Chuan Yu, Jian Xu, Fan Wu, Guihai Chen, Xiaoqiang Zhu.
In WSDM 2022. [Download paper]Neural Auction: End-to-End Learning of Auction Mechanisms for E-Commerce Advertising
Xiangyu Liu, Chuan Yu, Zhilin Zhang, Zhenzhe Zheng, Yu Rong, Hongtao Lv, Da Huo, Yiqing Wang, Dagui Chen, Jian Xu, Fan Wu, Guihai Chen, Xiaoqiang Zhu.
In KDD 2021. [Download paper] [slide] [video]Optimizing Multiple Performance Metrics with Deep GSP Auctions for E-commerce Advertising
Xiangyu Liu*, Zhilin Zhang*, Zhenzhe Zheng, Chenrui Zhang, Miao Xu, Junwei Pan, Chuan Yu, Fan Wu, Jian Xu, Kun Gai.
In WSDM 2021. [Download paper] [slide] [video]Feudal Latent Space Exploration for Coordinated Multi-agent Reinforcement Learning
Xiangyu Liu, Ying Tan.
In AAMAS@ALA 2020. [Download paper]Attentive relational state representation in decentralized multiagent reinforcement learning
Xiangyu Liu, Ying Tan.
In IEEE Transactions on Cybernetics (TCYB, IF=11.448) 2020. [Download paper]Learning Distributed Coordinated Policy in Catching Game with Multi-Agent Reinforcement Learning
Xiangyu Liu, Ying Tan.
In IJCNN 2019. [Download paper]Multi-source, Multi-object and Multi-domain (M-SOD) Electromagnetic Interference System Optimised by Intelligent Optimisation Approaches
Yihua Hu, Minle Li, Xiangyu Liu, Ying Tan.
In Natural Computing 2020. [Download paper]Adaptive potential fields model for solving distributed area coverage problem in swarm robotics
Xiangyu Liu, Ying Tan.
In ICSI 2017. [Download paper]
Academic visits, internships, and industry collaborations
- Research collaboration with Advanced Network Lab @ SJTU for learning-based mechanism design in e-commerce advertising under supervision of Dr. Zhenzhe Zheng, 2020-2021.
- Research intern at Alibaba for reinforcement learning in e-commerce, 2019.
- Research intern at Horizon Robotics for reinforcement learning and its applications in autonomous vehicles and game AI, 2016-2019.
Academic Services
- Conference Reviewer (Program Committee Member): WWW 2022, WCCI 2022, ECML-PKDD 2022, IJCAI 2023, KDD 2023.
- Journal Reviewer: IEEE Trans. on Cybernetics (TCYB), Natural Computing.