Please wait a minute...
文章检索
复杂系统与复杂性科学  2020, Vol. 17 Issue (2): 47-53    DOI: 10.13306/j.1672-3813.2020.02.006
  本期目录 | 过刊浏览 | 高级检索 |
带攻击玩家的演化拥塞博弈的鲁棒性分析
王桂林, 徐勇
河北工业大学理学院,天津 300401
Robustness Analysis of Evolutionary Congestion Game with Attackers
WANG Guilin, XU Yong
School of Science, Hebei University of Technology, Tianjin 300401, China
全文: PDF(937 KB)  
输出: BibTeX | EndNote (RIS)      
摘要 针对带有攻击玩家和可行状态受限集的演化拥塞博弈,利用矩阵的半张量积方法,将博弈动态系统代数公式化并研究其鲁棒性问题。首先,将带有攻击玩家和控制玩家的演化拥塞博弈表示成代数形式;然后,设计开环控制和状态反馈控制,使可行状态受限集中的任意初始局势能鲁棒可达纳什均衡。最后,通过例子说明带有攻击玩家的演化拥塞博弈的动态系统在开环控制和状态反馈控制下能鲁棒可达纳什均衡。
服务
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章
王桂林
徐勇
关键词 演化博弈拥塞博弈攻击玩家可行状态受限集开环控制状态反馈控制矩阵半张量积    
Abstract:The evolutionary congestion game with attackers and feasible state constrained set is investigated, using the semi-tensor product method of matrix, game dynamic system is transformed into an algebraic form and studied its robustness. Firstly, evolutionary congestion game with attackers and controllers is transformed into an algebraic form. Secondly, the open-loop control and state feedback control are transformed, and the Nash equilibrium is robust for any initial profiles in the restricted set of feasible states. Finally, an example is presented to illustrate that the dynamic system of evolutionary congestion game with attackers can achieve robust reachable equilibrium under open-loop control and state feedback control.
Key wordsevolutionary games    congestion games    attacker    feasible state constrained set    open-loop control    state feedback control    semi-tensor product of matrices
     出版日期: 2020-06-24
ZTFLH:  O225  
通讯作者: 徐勇(1971),男,山东蒙阴人,博士,教授,主要研究方向为非线性系统、复杂网络等。   
作者简介: 王桂林(1993),女,山西大同人,硕士研究生,主要研究方向为拥塞博弈的理论及应用。
引用本文:   
王桂林, 徐勇. 带攻击玩家的演化拥塞博弈的鲁棒性分析[J]. 复杂系统与复杂性科学, 2020, 17(2): 47-53.
WANG Guilin, XU Yong. Robustness Analysis of Evolutionary Congestion Game with Attackers. Complex Systems and Complexity Science, 2020, 17(2): 47-53.
链接本文:  
http://fzkx.qdu.edu.cn/CN/10.13306/j.1672-3813.2020.02.006      或      http://fzkx.qdu.edu.cn/CN/Y2020/V17/I2/47
[1]Rosenthal R W. A class of games possessing pure-strategy Nash equilibriam[J]. International Journal of Game Theory, 1973, 2(1): 6567.
[2]Imane D B, Abdelfettah M. 5G-dynamic resource sharing mechanism for vehicular networks: congestion game approach[C]. International Symposium on Advanced Electrical and Communication Technologies (ISAECT), 2018: 15.
[3]Tatsuya I, Yukihiro T, Daisuke F. Self-fulfilling signal of an endogenous state in network congestion games[J]. Networks and Spatial Economics, 2017, 17(3): 889909.
[4]刘觉夫, 陈晓. 基于空间拥塞博弈的自适应负载频谱算法研究[J]. 计算机工程与科学, 2013, 35(7): 6470.
Liu Juefu, Chen Xiao. Research on adaptive load spectrum algorithms based on spatial congestion game[J]. Computer Engineering and Science, 2013, 35(7): 6470.
[5]王祖喜, 邓昭彰, 李力. 基于局域信息少数者博弈的拥塞控制算法[J]. 通信学报, 2014, 35(1): 148166.
Wang Zhuxi, Deng Zhaozhang, Li Li. Congestion control algorithm based on local information minority game[J]. Journal of Communications, 2014, 35(1): 148166.
[6]Marden J R, Wierman A. Distributed welfare games[J]. Operations Research, 2013, 61(1): 155168.
[7]Wang Y H, Cheng D Z. Stability and stabilization of a class of finite evolutionary games[J]. Journal of the Franklin Institute, 2017, 354(3): 16031617.
[8]Fu S H. Modeling, analysis and optimization of a type of evolutionary public goods games[C]. Chinese Automation Congress, Jinan, China, 2017.
[9]Cheng D Z, He F H, Qi H S, et al. Modeling, analysis and control of networked evolutionary games[J]. IEEE Transactions on Automatic Control, 2015, 60(9): 24022415.
[10] Mao Y, Wang L Q, Liu Y, et al. Stabilization of evolutionary networked games with length-r information[J]. Applied Mathematics and Computation, 2018, 377: 442451.
[11] Fu S H, Zhao G D, Li H T, et al. Model and control for a class of networked evolutionary games with finite memories and time-varying networks[J]. Circuits Systems and Signal Processing, 2018, 37(7): 30933114.
[12] Zhao G D, Li H T, Sun W W, et al. Modelling and strategy consensus for a class of networked evolutionary games[J]. Journal International Journal of Systems Science, 2018, 49(12): 25482557.
[13] Zhang K Z, Xiao N, Xie L H. Convergence speed analysis for evolutionary congestion games[C]. The 10th Asian Control Conference, Kota Kinabalu, 2015: 15.
[14] Hao Y Q, Pan S S, Qiao Y P, et al. Cooperative control via congestion game approach[J]. IEEE Transactions on Automatic Control, 2016, 63(12): 18.
[15] Zhong J, Liu Y, Kou K I. On the ensemble controllability of Boolean control networks using STP method[J]. Applied Mathematics and Computation, 2019, 358: 5162.
[16] Liu H C, Liu Y, Li Y Y. Observability of Boolean networks via STP and graph methods[J]. IET Control Theory and Applications, 2019, 13(7): 10311037.
[17] Liu R J, Lu J Q, Liu Y, et al. Delayed feedback control for stabilization of Boolean control networks with state delay[J]. IEEE Transactions on Neural Networks and Learning Systems, 2018, 29(7): 3283 3288.
[18] Yu Y Y, Meng M, Feng J E, et al. Stabilizability analysis and switching signals design of switched Boolean networks[J]. Nonlinear AnalysisHybrid Systems. 2018, 30: 3144.
[19] Sylvain C,Satoru T. Robustness to incomplete information in repeated games[J]. Theoretical Economics, 2011, 6: 4993.
[20] Zhang X, Hao Y Q, Cheng D Z. Incomplete potential game[C]. Proceedings of the 36th Chinese Control Conference, Dalian, China, 2017.
[21] Li B W, Lu J Q, Liu Y. The local convergence of boolean networks with disturbances[J]. IEEE Transactions on Circuits and Systems II-Express Briefs, 2019, 66(4): 667671.
[22] Li B W, Liu Y, Lou J G, et al. The robustness of outputs with respect to disturbances for boolean control networks[J]. IEEE Transactions on Neural Networks and Learning Systems, 2019: 16.
[23] Li Y L, Ding X Y, Li H T. Robust consensus of networked evolutionary games with attackers and forbidden profiles[J]. Entropy, 2018: 113.
[24] Cheng D Z, Qi H S. Analysis and Control of Boolean Networks: A Semi-tensor Product Approach[M]. London: Springer, 2011.
[25] John F N . Non-cooperative game[J]. The Annals of Mathematics, 1951, 54(2): 286295.
[1] 芮晨, 张胜发, 陶富, 张维军, 田东华. 基于患者动态知识搜索的医生过度医疗行为研究[J]. 复杂系统与复杂性科学, 2020, 17(2): 86-92.
[2] 全吉, 周亚文, 王先甲. 社会困境博弈中群体合作行为演化研究综述[J]. 复杂系统与复杂性科学, 2020, 17(1): 1-14.
[3] 章平, 黄傲霜, 罗宏维. 不同类型复杂网络中个体合作行为互动的演化博弈模拟[J]. 复杂系统与复杂性科学, 2019, 16(3): 60-70.
[4] 李春发, 王学敏, 来茜茜, 薛楠楠. “互联网+”手机回收模式缘何绩效不彰?——基于mABM的演化博弈仿真分析[J]. 复杂系统与复杂性科学, 2019, 16(1): 63-73.
[5] 苏雪, 徐勇, 樊旭娇. 切换拓扑企业创新时滞演化博弈[J]. 复杂系统与复杂性科学, 2019, 16(1): 54-62.
[6] 李杰, 张睿, 徐勇. 虚假口碑信息控制演化博弈研究[J]. 复杂系统与复杂性科学, 2018, 15(3): 39-46.
[7] 肖琴, 罗帆. 机场外来物风险监管策略的演化博弈研究[J]. 复杂系统与复杂性科学, 2018, 15(2): 18-25.
[8] 武利琴, 王金环, 徐勇. 一种基于半张量积的多层网络演化博弈方法[J]. 复杂系统与复杂性科学, 2017, 14(3): 68-74.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed