个人简介
卢宗青现任北京大学计算机系数字媒体研究所研究员（“博雅青年学者”）、博士生导师，“决策智能”课题组负责人。他于2014年在新加坡南洋理工大学获得计算机博士学位，2014至2017年在美国宾州州立大学从事博士后研究，并于2017年9月加入北京大学。他在东南大学获得学士和硕士学位。担任NeurIPS、ICLR、IJCAI、AAMAS、INFOCOM等会议TPC，Nature Machine Intelligence等审稿人。
近期论文
查看导师最新文章
（温馨提示：请注意重名现象，建议点开原文通过作者单位确认）
Model-Based Decentralized Policy Optimization Hao Luo, Jiechuan Jiang, and Zongqing Lu arXiv:2302.08139
Learning Multi-Object Positional Relationships via Emergent Communication Yicheng Feng, Boshi An, and Zongqing Lu arXiv:2302.08084
Best Possible Q-Learning Jiechuan Jiang and Zongqing Lu arXiv:2302.01188
A Survey on Transformers in Reinforcement Learning Wenzhe Li, Hao Luo, Zichuan Lin, Chongjie Zhang, Zongqing Lu, and Deheng Ye arXiv:2301.03044
Decentralized Policy Optimization Kefan Su and Zongqing Lu arXiv:2211.03032
Multi-Agent Sequential Decision-Making via Communication Ziluo Ding, Kefan Su, Weixin Hong, Liwen Zhu, Tiejun Huang, and Zongqing Lu arXiv:2209.12713
MA2QL: A Minimalist Approach to Fully Decentralized Multi-Agent Reinforcement Learning Kefan Su, Siyuan Zhou, Jiechuan Jiang, Chuang Gan, Xiangjun Wang, and Zongqing Lu arXiv:2209.08244
Offline Decentralized Multi-Agent Reinforcement Learning Jiechuan Jiang and Zongqing Lu arXiv:2108.01832
[ACL'23] Multi-Agent Language Learning: Symbolic Mapping Yicheng Feng and Zongqing Lu 61st Annual Meeting of the Association for Computational Linguistics (ACL), July 9-14, 2023.
[ICML'23] Entity Divider with Language Grounding in Multi-Agent Reinforcement Learning Ziluo Ding, Wanpeng Zhang, Junpeng Yue, Xiangjun Wang, Tiejun Huang, and Zongqing Lu Fortieth International Conference on Machine Learning (ICML), July 23-29, 2023. (Acceptance Rate: 27.9%=1827⁄6538)
[CVPR'23] Multi-Agent Automated Machine Learning Zhaozhi Wang, Kefan Su, Jian Zhang, Huizhu Jia, Qixiang Ye, Xiaodong Xie, and Zongqing Lu IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR), Jun 18-22, 2023. (Acceptance Rate: 25.78%=2360⁄9155)
[ICLR'23] More Centralized Training, Still Decentralized Execution: Multi-Agent Conditional Policy Factorization Jiangxing Wang, Deheng Ye, and Zongqing Lu Eleventh International Conference on Learning Representations (ICLR), May 1-5, 2023.
[AAMAS'23] Adaptive Learning Rates for Multi-Agent Reinforcement Learning Jiechuan Jiang and Zongqing Lu Twenty-Second International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 29 - June 2, 2023. (Acceptance Rate: 23%=237⁄1015)
[AAAI'23] Online Tuning for Offline Decentralized Multi-Agent Reinforcement Learning Jiechuan Jiang and Zongqing Lu Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI), February 7-14, 2023. (Acceptance Rate: 19%=1721⁄8777)
[NIPS'22] I2Q: A Fully Decentralized Q-Learning Algorithm Jiechuan Jiang and Zongqing Lu Thirty-Sixth Annual Conference on Neural Information Processing Systems (NIPS), November 28 - December 9, 2022. (Acceptance Rate: 25.6%=2665⁄10411)
[NIPS'22] Model-Based Opponent Modeling Xiaopeng Yu, Jiechuan Jiang, Wanpeng Zhang, Haobin Jiang, and Zongqing Lu Thirty-Sixth Annual Conference on Neural Information Processing Systems (NIPS), November 28 - December 9, 2022. (Acceptance Rate: 25.6%=2665⁄10411)
[NIPS'22] Mildly Conservative Q-Learning for Offline Reinforcement Learning Jiafei Lyu, Xiaoteng Ma, Xiu Li, and Zongqing Lu Thirty-Sixth Annual Conference on Neural Information Processing Systems (NIPS), November 28 - December 9, 2022. (Acceptance Rate: 25.6%=2665⁄10411, spotlight)
[NIPS'22] Double Check Your State Before Trusting It: Confidence-Aware Bidirectional Offline Model-Based Imagination Jiafei Lyu, Xiu Li, and Zongqing Lu Thirty-Sixth Annual Conference on Neural Information Processing Systems (NIPS), November 28 - December 9, 2022. (Acceptance Rate: 25.6%=2665⁄10411, spotlight)
[NIPS'22] Learning to Share in Multi-Agent Reinforcement Learning Yuxuan Yi, Ge Li, Yaowei Wang, and Zongqing Lu Thirty-Sixth Annual Conference on Neural Information Processing Systems (NIPS), November 28 - December 9, 2022. (Acceptance Rate: 25.6%=2665⁄10411)
[NIPS'22] Towards Human-Level Bimanual Dexterous Manipulation with Reinforcement Learning Yuanpei Chen, Tianhao Wu, Shengjie Wang, Xidong Feng, Jiechuan Jiang, Stephen Marcus McAleer, Hao Dong, Zongqing Lu, Song-Chun Zhu, and Yaodong Yang Thirty-Sixth Annual Conference on Neural Information Processing Systems (NIPS), November 28 - December 9, 2022.
[ICML'22] Divergence-Regularized Multi-Agent Actor-Critic Kefan Su and Zongqing Lu Thirty-Ninth International Conference on Machine Learning (ICML), July 17-23, 2022 (Acceptance Rate: 22%=1235⁄5630)
[ICML'22] Robust Task Representations for Offline Meta-Reinforcement Learning via Contrastive Learning Haoqi Yuan and Zongqing Lu Thirty-Ninth International Conference on Machine Learning (ICML), July 17-23, 2022 (Acceptance Rate: 22%=1235⁄5630)
[ICML'22] Difference Advantage Estimation for Multi-Agent Policy Gradients Yueheng Li, Guangming Xie, and Zongqing Lu Thirty-Ninth International Conference on Machine Learning (ICML), July 17-23, 2022 (Acceptance Rate: 22%=1235⁄5630)
[ICML'21] The Emergence of Individuality Jiechuan Jiang and Zongqing Lu Thirty-Eighth International Conference on Machine Learning (ICML), July 18-24, 2021 (Acceptance Rate: 3%=166⁄5513, oral presentation)
[ICML'21] FOP: Factorizing Optimal Joint Policy of Maximum-Entropy Multi-Agent Reinforcement Learning Tianhao Zhang, Yueheng Li, Chen Wang, Guangming Xie and Zongqing Lu Thirty-Eighth International Conference on Machine Learning (ICML), July 18-24, 2021 (Acceptance Rate: 21%=1184⁄5513)
[AAAI'21] Hierarchically and Cooperatively Learning Traffic Signal Control Bingyu Xu, Yaowei Wang, Zhaozhi Wang, Huizhu Jia, and Zongqing Lu Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI), February 2-9, 2021. (Acceptance Rate: 21%=1692⁄7911)
[DATE'21] Asynchronous Reinforcement Learning Framework for Net Order Exploration in Detailed Routing Tong Qu, Yibo Lin, Zongqing Lu, Yajun Su, and Yayi Wei Design, Automation and Test in Europe Conference (DATE), February 1-5, 2021.
[NIPS'20] Learning Individually Inferred Communication for Multi-Agent Cooperation Ziluo Ding, Tiejun Huang, and Zongqing Lu Thirty-Fourth Annual Conference on Neural Information Processing Systems (NIPS), December 6-12, 2020. (Acceptance Rate: 1%=105⁄9454, oral)
[ICLR'20] Graph Convolutional Reinforcement Learning Jiechuan Jiang, Chen Dun, Tiejun Huang and Zongqing Lu International Conference on Learning Representation (ICLR), April 26-30, 2020. (Acceptance Rate: 26.5%=687⁄2594)
[AAAI'20] Generative Exploration and Exploitation Jiechuan Jiang and Zongqing Lu Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI), February 7-12, 2020. (Acceptance Rate: 21%=1591⁄7737)
[NIPS'19] Learning Fairness in Multi-Agent Systems Jiechuan Jiang and Zongqing Lu Thirty-Third Annual Conference on Neural Information Processing Systems (NIPS), December 8-14, 2019. (Acceptance Rate: 21%=1428⁄6743)
[BuildSys'19] Heterogeneous Transfer Learning for Thermal Comfort Modeling Weizheng Hu, Yong Luo, Zongqing Lu, and Yonggang Wen In Proceedings of ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation (BuildSys), November 13-14, 2019. (Acceptance Rate: 31%=40⁄131)
[NIPS'18] Learning Attentional Communication for Multi-Agent Cooperation Jiechuan Jiang and Zongqing Lu Thirty-Second Annual Conference on Neural Information Processing Systems (NIPS), December 3-8, 2018. (Acceptance Rate: 21%=1011⁄4856)
[INFOCOM'18] A Computing Platform for Video Crowdprocessing Using Deep Learning Zongqing Lu, Kevin Chan, and Thomas La Porta In Proceedings of IEEE International Conference on Computer Communications (INFOCOM), April 15-19, 2018. (Acceptance Rate: 19%=309⁄1606)
京公网安备 11010802027423号