谭少林

一、基本情况

谭少林,2014年博士毕业于中国科学院数学与系统科学研究院,2016年澳大利亚RMIT大学访问学者。现为湖南大学电气与信息工程学院副教授,机器人视觉感知与控制技术国家工程中心研究员,岳麓学者。中国运筹学会智能工业数据解析与优化专业委员会理事、中国指挥与控制学会网络科学与工程专业委员会委员。主要研究领域包括:--物安全交互、决策智能、多个体博弈对抗、图数据表示与学习、复杂网络。在IEEE TAC, IEEE TKDE, IEEE TNNLS, IEEE TC, SAIM JCO.等国际权威期刊发表论文60余篇,出版《复杂网络上的博弈及其演化动力学》专著一部。主持包括国家自然科学基金面上项目、青年项目等各类科研项目10余项。


二、主要研究方向及招生

多智能体博弈学习理论(Multi-agent Game Learning)、图数据表示与学习(Graph representation and Learning)、复杂系统与控制 (Theory and Control of Complex Systems)、多机器人协同与控制(Coordination and Control of multi-robotics) 及其在分布式协同控制中的应用(Distributed Cooperative Control)、智能控制与优化(Intelligent Control and Optimization)等。


科研经费充足,和中国科学院数学与系统科学研究院、武汉大学、西北工业大学、墨尔本皇家理工大学、南澳大学、香港城市大学等多个国内外相关研究团队保持着密切科研合作交流。常年招收自动化、计算机、数学、系统科学等相关专业的硕士研究生


欢迎感兴趣的同学联系:shaolintan@hnu.edu.cn

 

三、学习工作经历

20171 --- 至今,湖南大学,电气与信息工程学院,副教授

201512--- 201612月,澳大利亚RMIT大学,访问学者

20147--- 201612月,湖南大学,电气与信息工程学院,助理教授

20099--- 20147月,中国科学院数学与系统科学研究院,系统控制重点实验室,博士

 

四、主持项目

1. 湖南省自然科学基金优秀青年项目,2022.01---2024.12,主持

2. 国家自然科学基金面上项目,2019.01---2022.12,主持

3. 国家自然科学基金青年项目,2016.01---2018.12,主持

4. 湖南省自然科学基金青年项目,2016.01---2018.12,主持

5. 中国博士后科学基金特别资助,2016.05---2017.05, 主持

6. 中国博士后科学基金一等面上资助,2015.11---2016.11,主持

7. 中央高校基本业务费,2014.07-2018.12,主持

 

五、主要论文

专著:

[1] 吕金虎,谭少林,《复杂网络上的博弈及其演化动力学》,高等教育出版社出版,2019


期刊文章

[1] Shaolin Tan, Zhihong Fang, Yaonan Wang, and Jinhu Lu, “A Timestamp-Based Inertial Best-Response Dynamics for Distributed Nash Equilibrium Seeking in Weakly Acyclic Games,” IEEE Transactions on Neural Networks and Learning Systems, doi: 10.1109/TNNLS.2022.3183250, 2022.

[2] Shaolin Tan, Zhihong Fang, Yaonan Wang, and Jinhu Lu, “An Augmented Game Approach for Design and Analysis of Distributed Learning Dynamics in Multiagent Games,” IEEE Transactions on Cybernetics, doi: 10.1109/TCYB.2022.3174196, 2022.

[3] Zhihong Fang, Shaolin Tan*, Yaonan Wang, and Jinhu Lu, “Elementary Subgraph Features for Link Prediction with Neural Networks,” IEEE Transactions on Knowledge and Data Engineering, doi: 10.1109/TKDE.2021.3132352, 2021.

[4] Shaolin Tan, and Yaonan Wang, “A Payoff-Based Learning Approach for Nash Equilibrium Seeking in Continuous Potential Games,” Neurocomputing, vol. 468, no.11, pp. 431-440, 2022.

[5] Shaolin Tan, Yaonan Wang, and A. V. Vasilakos, “Distributed Population Dynamics for Searching Generalized Nash Equilibria of Population Games With Graphical Strategy Interactions,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 52, no.5, pp. 3263--3272, 2022.

[6] Shaolin Tan, and Yaonan Wang, “Graphical Nash Equilibria and Replicator Dynamics on Complex Networks,” IEEE Transactions on Neural Networks and Learning Systems, vol. 31, no.6, pp. 1831 - 1842, 2020.

[7] Shaolin Tan, “Proximity inheritance explains the evolution of cooperation under natural selection and mutation,” Proceedings of the Royal Society B: Biological Sciences, vol. 286, no. 1902: 20190690, 2019.

[8] Shaolin Tan, Yaonan Wang, Yao Chen, and Zhen Wang, “Evolutionary dynamics of collective behavior selection and drift: Flocking, collapse, and oscillation,” IEEE Transactions on Cybernetics, vol. 47, no.7, pp. 1694-1705, 2017.

[9] Shaolin Tan, Jinhu Lü, and Zongli Lin, “Emerging behavioral consensus of evolutionary dynamics on complex networks,” SIAM Journal on Control and Optimization, vol. 54, no. 6, pp. 3258-3272, 2016.

[10] Shaolin Tan and Jinhu Lü, “Analysis and control of networked game dynamics via a microscopic deterministic approach,” IEEE Transactions on Automatic Control, vol. 61, no. 12, pp. 4118-4124, 2016.

[11] Shaolin Tan, Yaonan Wang, and Yao Chen, “A unified tractable approach for random drifts on dynamical networks,” IEEE Transactions on Circuits and Systems II, vol. 63, no. 3, pp. 299-303, 2016.

[12] Shaolin Tan and Jinhu Lü, “An evolutionary game approach for determination of the structural conflicts in signed networks,” Scientific Reports, doi: 10.1038/srep22022, 2016.

[13] Shaolin Tan, Jinhu Lü, and David John Hill, “Towards a theoretical framework for analysis and intervention of random drift on complex networks,” IEEE Transactions on Automatic Control, vol. 60, no. 2, pp. 576-581, 2015. (ESI高被引论文)

[14] Shaolin Tan and Jinhu Lü, “Characterizing the effect of population heterogeneity on evolutionary dynamics on complex networks,” Scientific Reports, vol. 4, art. no. 5034, 2014.

[15] Shaolin Tan, Jinhu Lü, Guanrong Chen, and David John Hill, “When structure meets function in evolutionary dynamics on complex networks,” IEEE Circuits and Systems Magazine, vol. 14, no. 4, pp. 36-50, 2014.

[16] Shaolin Tan, Jinhu Lü, Xinghuo Yu, and David John Hill, “Evolution and main-tenance of cooperation via inheritance of neighborhood relationship,” Chinese Science Bulletin, vol. 58, no. 28-29, pp. 3491-3498, 2013.

[17] Shaolin Tan, Shasha Feng, Pei Wang, and Yao Chen, “Strategy selection in evolutionary game dynamics on group interaction networks,” Bulletin of Mathematical Biology, vol. 76, no. 11, pp. 2785-2805, 2014.

中文文章:

[18] 谭少林,吕金虎,复杂网络上的演化博弈动力学---一个计算视角的综述,《复杂系统与复杂性科学》,20174):1-13

[19] 谭少林,吕金虎,复杂网络上合作行为的涌现,《中国自动化学会通讯》,201334):37-41


书籍章节:

[20] Shaolin Tan, Jinhu Lü, “Strategy Selection in Networked Evolutionary Games: Structural Effect and the Evolution of Cooperation” in Complex Systems and Networks: Dynamics, Controls and Applications, Edited by J. Lü, X. Yu, G. Chen, W. Yu, Springer-Verlag, Germany, Oct. 2015, pp. 439-459

 

 

 

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