经济系统中,个体相互作用能够给群体涌现非常复杂的非线性行为,导致某些个体的非理性行为可能导致整个经济系统迅速崩溃,这种崩溃前系统的临界状态就显得异常重要.为了得到比较深刻的结论,将经济系统中个体之间的相互作用抽象成以随机复杂网络为结构的自适应博弈模型,从而构建合理的复杂自适应系统理论模型,然后通过随机攻击与蓄意攻击,来确定这一系统逾渗的临界状态.分析认为,当系统受到随机攻击时,系统表现出很强的鲁棒性,然而当系统受到蓄意攻击时,存在一个临界攻击概率使得系统具有较强的临界性.结论认为,系统受到随机攻击时,至少有两个大的组分保持系统联通,然而,当系统受到蓄意攻击时,系统存在一个临界删除概率,当删除概率小于这一临界概率时,系统存在两个大的组分;当删除概率大于这一临界概率时,系统难以保持联通.进一步而言,这一临界概率与系统中Agent的收益相关,这一结论修订了经典的以度为函数的复杂网络中的临界概率.
Abstract
Agents' irrational behavior would lead to local configuration of complex adaptive system changed, which makes the system percolation, the criticality of system percolation is critical to make decision for improve the system or keep the system from being collapsed out of the blue and sharply. To draw a profound conclusion, a complex adaptive system model with agent's behavior and its local configuration co-evolved is constructed to describe how an arbitrary agent and its neighbors change their strategy and local interactive configuration, then the percolation critical point of this system can be gotten by considering it is attacked randomly and intentionally. It is shown that, after analyzing, the system is robust when it is attacked randomly, however, it is vulnerable when it is attacked intentionally. It is concluded that: when the system is attacked randomly, there are at least two large components keep the system connected in this system; however, when the system is attacked intentionally, the system has the critical point with deleting agents, which means that there are two large components keep the system connected in this system if the deleting probability is smaller than the critical probability and the system cannot be connected if the deleting probability is larger than the critical probability. Furthermore, the corresponding critical probability is driven by agents' payment, this conclusion revises the classic one decided by degree.
关键词
Agent /
经济复杂自适应系统 /
对称性破缺 /
临界
{{custom_keyword}} /
Key words
Agent /
economical complex adaptive system /
symmetry breaking /
criticality
{{custom_keyword}} /
中图分类号：
N94-02
TP271.74
{{custom_clc.code}}
({{custom_clc.text}})
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
参考文献
[1] 赵奕奕, 彭怡,肖磊,等. 突发事件下群体抢购行为的舆论传播机理研究[J]. 系统工程理论与实践, 2015, 35(3):616-622.Zhao Y Y, Peng Y, Xiao L, et al. On opinion propagation mechanism of collective panic buying under emergences[J]. Systems Engineering-Theory & Practice, 2015, 35(3):616-622.
[2] 王筱莉,赵来军,谢婉林. 无标度网络中遗忘率变化的谣言传播模型研究[J]. 系统工程理论与实践, 2015, 35(2):458-465.Wang X L, Zhao L J, Xie W L. Rumor spreading model with variable forgetting rate in scale-free network[J]. Systems Engineering-Theory & Practice, 2015, 35(2):458-465.
[3] 郑君君,何鸿勇,张平. 基于无标度网络与观点传播动力学的股权拍卖机制设计与仿真研究[J]. 系统工程理论与实践, 2015, 35(8):2044-2053.Zheng J J, He H Y, Zhang P. Research on mechanism design and simulation of equity auction based on scale-free network and dynamics of opinion spread[J]. Systems Engineering-Theory & Practice, 2015, 35(8):2044-2053.
[4] 张耀峰, 肖人彬. 基于元胞自动机的网络群体事件舆论同步的涌现机制[J]. 系统工程理论与实践, 2014, 34(10):2600-2608.Zhang Y F, Xiao R B. Emergence mechanism of consensus synchronization in Internet collective behavior based on cellular automata[J]. Systems Engineering-Theory & Practice, 2014, 34(10):2600-2608.
[5] Schelling T C. Micromotives and macrobehavior[M]. New York:W. W. Norton & Company, 1921.
[6] 菲利普·鲍尔. 预知社会——群体行为的内在法则[M].暴永宁,译. 当代中国出版社, 2007.Ball P. Critical mass:How one thing leads to another[M]. Contemporary China Publishing Home, 2007.
[7] Bollobás B, Riordan O. Robustness and vulnerability of scale-free random graphs[J]. Internet Mathematics, 2007, 1(1):1-35.
[8] Bollobás B, Riordan O. Sparse graphs:Metrics and random models[J]. Random Structure and Algorithms, 2011, 39(1):1-38.
[9] Bollobás B, Kozma R, Miklas P. Handbook of large-scale random networks[M]. Springer, New York, 2008.
[10] Boccalett S, Latora V, Moreno Y, et al. Complex networks:Structure and dynamics[J]. Physics Reports, 2006(424):175-308.
[11] Li D, Havlin S, Boccaletti S. Entrainment competition in complex networks[J]. International Journal of Bifurcation and Chaos, 2010, 20(3):827-833.
[12] 杨孟,傅新楚,吴庆初. 复杂网络上带传播媒介SIS模型的全局稳定性[J]. 系统工程学报, 2010, 25(6):767-773.Yang M, Fu X C, Wu Q C. Global stability of SIS epidemic model with infective medium on complex networks[J]. Journal of Systems Engineering, 2010, 25(6):767-773.
[13] Hu K, Hu T, Tang Y. Cascade defense via control of the fluxes in complex networks[J]. Journal of Statistical Physics, 2010, 141:555-565.
[14] 何大韧,刘宗华,汪秉宏. 复杂网络研究的一些统计物理学方法及其背景[J]. 力学进展, 2008, 38(6):5-14.He D R, Liu Z H, Wang B H. Some statistical physics methods for investigations of complex networks and their background[J]. Advances in Mechanics, 2008, 38(6):5-14.
[15] 叶东海, 蒋国平, 宋玉蓉. 多局域世界复杂网络中的病毒传播研究[J]. 计算机工程, 2010, 36(23):130-132.Ye D H, Jiang G P, Song Y R. Research on virus spreading in multi local world complex network[J]. Computer Engineering, 2010, 36(23):130-132.
[16] 王增芳, 高卓, 潘晶财. 距离依赖的复杂网络上的Ising模型相变[J]. 北京师范大学学报(自然科学版), 2007, 43(1):34-36.Wang Z F, Gao Z, Pan J C. Phase transition in Ising model on complex networks with a range-dependent connection probability[J]. Journal of Beijing Normal University (Natural Science), 2007, 43(1):34-36.
[17] 于强,帅典勋,韩卫丽. 自相似数据流下的网络相变与临界现象[J]. 系统工程学报, 2003, 18(6):535-540.Yu Q, Shuai D X, Han W L. Network phase transitions and critical behaviors under self-similar traffic model[J]. Journal of Systems Engineering, 2003, 18(6):535-540.
[18] Ghoshal G, Bárabási A L. Ranking stability and super-stable nodes in complex networks[J]. Nature Communications, 2011, 2:1-7.
[19] Barabási A L. The origin of bursts and heavy tails in human dynamics[J]. Nature, 435(12):207-211.
[20] Zheng X, Xu X, Luo C C. Agent behaviors and coordinative mechanism[J]. Kybernetes, 2012, 41(10):1586-1603.
[21] Zheng X J. Invariable distribution of co-evolutionary complex adaptive system with agent behavior and local topological configuration[C]//Proceeding of the Forth International Conference of Complex Science Management and Risk, Toroto, 1-15.
[22] 郑小京. 经济与管理复杂自适应系统:个体行为、群体状态及演化[M]. 北京:科学出版社, 2014.Zheng X J. Complex adaptive system of economic and management:Individual behavior, collective state and the corresponding evolution[M]. Beijing:Science Press, 2004.
{{custom_fnGroup.title_cn}}
脚注
{{custom_fn.content}}
基金
国家自然科学基金(71371147)
{{custom_fund}}
PDF(1924 KB)
