[1]武利琴,徐勇,王金环,等.基于半张量积的企业创新网络演化博弈[J].智能系统学报,2018,13(5):776-782.[doi:10.11992/tis.201706064]
WU Liqin,XU Yong,WANG Jinhuan,et al.Evolutionary enterprise innovation networked game based on the semi-tensor product of matrices[J].CAAI Transactions on Intelligent Systems,2018,13(5):776-782.[doi:10.11992/tis.201706064]
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WU Liqin,XU Yong,WANG Jinhuan,et al.Evolutionary enterprise innovation networked game based on the semi-tensor product of matrices[J].CAAI Transactions on Intelligent Systems,2018,13(5):776-782.[doi:10.11992/tis.201706064]
基于半张量积的企业创新网络演化博弈
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
13
期数:
2018年第5期
页码:
776-782
栏目:
学术论文—智能系统
出版日期:
2018-09-05
- Title:
- Evolutionary enterprise innovation networked game based on the semi-tensor product of matrices
- Keywords:
- enterprise innovation; semi-tensor product; innovation networks; evolutionary game; Nash equilibrium; government regulation; Boxed Pig game; strategy profile
- 分类号:
- F270;TP18
- 摘要:
- 当代经济环境下，创新已经成为企业生存发展的必要条件。将所有企业按规模分为大小两种企业，建立企业创新双层耦合网络，并研究了企业间的博弈过程。首先，运用矩阵半张量积方法，以“智猪博弈”为基本博弈，得到每一时刻各企业的策略，而非企业总体创新的比例；其次，根据收益函数得到整个企业创新网络的最优稳定纳什均衡点；最后，增加政府调控，改变博弈基本支付矩阵，从而达到最优稳定纳什均衡状态，即所有企业全部创新。
- Abstract:
- In the contemporary economic environment, innovation has become the inevitable condition for the survival and development of enterprises. In this paper, all the enterprises were classified into two categories according to the scale, establishing a double-layer coupling network of enterprise innovation, and the process of the game between enterprises was studied. Firstly, taking "Boxed Pig Game" as the basic game, the semi-tensor product method was used to get the strategy of each enterprise at every moment, not the proportion of the enterprise overall innovation. Secondly, the optimal stability for the Nash equilibrium of the whole enterprise innovation network was reached according to the payoff function. Finally, the government regulation was introduced to change the basic matrix of the game and therefore reach a stable state of the optimal Nash equilibrium; that is, all enterprises realized innovation all round.
- 参考文献/References:
-
[1] WU Qingchu, LOU Yijun, ZHU Wenfang. Epidemic outbreak for an SIS model in multiplex networks with immunization[J]. Mathematical biosciences, 2016, 277:38-46.
[2] WANG Danzhu, LANG M X, SUN Yan. Evolutionary game analysis of co-opetition relationship between regional logistics nodes[J]. Journal of applied research and technology, 2014, 12(2):251-260.
[3] ETESAMI S R, BASAR T. Complexity of equilibrium in diffusion games on social networks[C]//Proceedings of 2014 American Control Conference. Portland, USA, 2014:2065-2070.
[4] YAN Yongyi, CHEN Zengqiang, YUE Jumei. STP approach to controlliability of finite state machines[J]. Ifac-PapersonLine, 2015, 48(28):138-143.
[5] 于斌斌, 余雷. 基于演化博弈的集群企业创新模式选择研究[J]. 科研管理, 2015, 36(4):30-38 YU Binbin, YU Lei. A study on cluster enterprise technology innovation selection based on the evolutionary game[J]. Science research management, 2015, 36(4):30-38
[6] ZHOU Qing, FANG Gang, WANG Dongpeng, et al. Research on the robust optimization of the enterprise’s decision on the investment to the collaborative innovation:under the risk constraints[J]. Chaos, solitons and fractals, 2016, 89:284-289.
[7] 盛光华, 张志远. 补贴方式对创新模式选择影响的演化博弈研究[J]. 管理科学学报, 2015, 18(9):34-45 SHENG Guanghua, ZHANG Zhiyuan. Allowance method’s influence on the innovation model choice in evolutionary game[J]. Journal of management sciences in China, 2015, 18(9):34-45
[8] 王健, 赵凯. "智猪博弈"下的合作创新研究——基于非对称演化博弈的分析[J]. 科技与经济, 2016, 29(2):21-25 WANG Jian, ZHAO Kai. Cooperative innovation of enterprises under "Boxed pig Game"-a research based on asymmetric evolutionary game[J]. Science and technology and economy, 2016, 29(2):21-25
[9] LIU Mengmeng, MA Yinghong, LIU Zhiyuan, et al. An IUR evolutionary game model on the patent cooperate of Shandong China[J]. Physic A:statistical mechanics and its applications, 2017, 475:11-23.
[10] CHENG Daizhan, XU Tingting, QI Hongsheng. Evolutionary stability strategy of networked evolutionary games[J]. IEEE transactions on neural networks and learning systems, 2014, 25(7):1335-1345.
[11] CHENG Daizhan, HE Fenghua, QI Hongsheng, et al. Modeling, analysis and control of networked evolutionary games[J]. IEEE transactions on automatic control, 2015, 60(9):2402-2415.
[12] CHENG Daizhan, QI Hongsheng, HE F, et al. Semi-tensor product approach to networked evolutionary games[J]. Control theory and technology, 2014, 12(2):198-214.
[13] CHENG Daizhan, XU Tingting, HE Fenghua, et al. On dynamics and Nash equilibriums of networked games[J]. IEEE/CAA journal of automatica sinica, 2014, 1(1):10-18.
[14] ZHAO Yin, GHOSH B K, CHENG Daizhan. Control of large-scale Boolean networks via network aggregation[J]. IEEE transactions on neural networks and learning systems, 2016, 27(7):1527-1536.
[15] LI Haitao, WANG Yuzhen, XIE Lihua. Output tracking control of Boolean control networks via state feedback:constant reference signal case[J]. Automatica, 2015, 59:54-59.
[16] LI Haitao, XIE Lihua, WANG Yuzhen. On robust control invariance of Boolean control networks[J]. Automatica, 2016, 68:392-396.
[17] CHENG Daizhan, ZHAO Yin, XU Tingting. Receding horizon based feedback optimization for mix-valued logical networks[J]. IEEE transactions on automatic control, 2015, 60(12):3362-3366.
[18] GUO Peilian, WANG Yuzhen, JIANG Ping. Nash equilibrium, dynamics and control of evolutionary networked games with multi-group[C]//Proceedings of the 35th Chinese Control Conference. Chengdu, China, 2016:585-590.
[19] GUO Peilian, WANG Yuzhen, LI Haitao. Algebraic formulation and strategy optimization for a class of evolutionary networked games via semi-tensor product method[J]. Automatic, 2013, 49(11):3384-3389.
[20] ZHAO Guodong, WANG Yuzhen. Formulation and optimization control of a class of networked evolutionary games with switched topologies[J]. Nonlinear analysis:hybrid systems, 2016, 22:98-107.
[21] ZHU Bing, XIA Xiaohua, WU Zhou. Evolutionary game theoretic demand-side management and control for a class of networked smart grid[J]. Automatic, 2016, 70:94-100.
[22] FU Shihua, WANG Yuzhen, ZHAO Guodong. A matrix approach to the analysis and control of networked evolutionary games with bankruptcy mechanism[J]. Asian journal of control, 2017, 19(2):717-727.
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备注/Memo
收稿日期:2017-06-19。
基金项目:国家社会科学基金项目（16FGL014）；国家自然科学基金项目（61203142）；河北省自然科学基金项目（F2014202206）.
作者简介:武利琴,女,1992年生,硕士研究生,主要研究方向为网络演化博弈及应用;徐勇,男,1971年生,教授,博士,主要研究方向为非线性系统控制、图论、复杂网络控制与优化。参加或主持省部级科研项目10余项,发表学术论文30余篇,被EI检索10余篇;王金环,女,1980年生,副教授,博士,主要研究方向为多智能体系统协同控制、网络演化博弈。主持国家级、省部级科研项目4项,发表学术论文30余篇,被SCI和EI收录30余篇。
通讯作者:徐勇.E-mail:xuyong@hebut.edu.cn.
更新日期/Last Update:
2018-10-25