姓名：王巍
籍贯：湖北应城职称：讲师民族：汉系：大数据管理与应用
E-mail：imagef@zuel.edu.cn
研究方向：机器学习（侧重强化学习）、多机器人系统决策与控制、文本挖掘、智能控制
社会兼职：IEEE TNNLS, IEEE SMCA, IEEE TC, Neurocomputing, IJSS等期刊审稿人
个人简历
教育背景：
2013.09-2019.06中国地质大学（武汉）自动化学院，控制科学与工程专业，博士学位
2009.09-2013.06中国地质大学（武汉）机械与电子信息工程学院，自动化专业，学士学位
工作经历：
2019.07-2021.02中冶南方工程技术有限公司，二级研究员
2021-03至今 中南财经政法大学 奔驰彩票计划 讲师
个人荣誉
“中国地质大学（武汉）优秀博士论文“奖
学术成果
期刊论文
1. Wei Wang, Xin Chen, Hao Fu, and Min Wu, Data-Driven Adaptive Dynamic Programming for Partially Observable Nonzero-Sum Games via Q-learning Method, International Journal of Systems Science, 2019, 50(7): 1338-1352.
2. Wei Wang, and Xin Chen, Model-Free Optimal Containment Control of Multi-Agent Systems Based on Actor-Critic Framework, Neurocomputing, 2018, 314: 242-250.
3. Wei Wang, Xin Chen, and Hao Fu, Model-Free Distributed Consensus Control Based on Actor-Critic Framework for Discrete-Time Nonlinear Multiagent Systems, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2020, 50(11): 4123-4134.
4. Wei Wang, Xin Chen, and Jianxin He, Adaptive Critic Design with Local Gaussian Process Models, Journal of Advanced Computational Intelligence and Intelligent Informatics, 2016, 20(7): 1135-1140.
5. Xin Chen, Wei Wang, Weihua Cao, and Min Wu, Gaussian-Kernel-Based Adaptive Critic Design Using Two-Phase Value Iteration, Information Sciences, 2019, 482: 139-155.
6. Yipu Sun, Xin Chen, Wei Wang, Hao Fu, and Min Wu, Model-Free Output Consensus Control for Partially Observable Heterogeneous Multivehicle Systems, IEEE Internet of Things Journal, 2020, 7(8): 7135-7147.
会议论文
1. Wei Wang, Changyang Feng, and Wei Quan, Data-Driven Control of a Class of Discrete-Time Linear Complex Dynamical Networks, in Proceedings of the 2019 IEEE International Conference on Big Data, 2019: 6243-6245.
2. Wei Wang, Xin Chen, Fang Wang, and Hao Fu, ADP-Based Model Reference Adaptive Control Design for Unknown Discrete-Time Nonlinear Systems, in Proceedings of the 2018 Chinese Control Conference, 2018: 8049-8054.
3. Wei Wang, Xin Chen, Luefeng Chen, and Min Wu, Model-Free Optimal Consensus Control for Multi-Agent Systems Using Kernel-Based ADP Method, in Proceedings of the 2017 IEEE Conference on Systems, Man, Cybernetics, 2017: 2471-2476.
