Computer Engineering and Applications ›› 2011, Vol. 47 ›› Issue (25): 5-9.

• 博士论坛 • Previous Articles     Next Articles

Improved self-propelled particle models and group behavior analysis

YAO Canzhong1,YANG Jianmei2   

  1. 1.School of Economics and Commerce,South China University of Technology,Guangzhou 510006,China
    2.School of Business Administration,South China University of Technology,Guangzhou 510640,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2011-09-01 Published:2011-09-01

改进的自推动粒子模型与群体行为研究

姚灿中1,杨建梅2   

  1. 1.华南理工大学 经济与贸易学院,广州 510006
    2.华南理工大学 工商管理学院,广州 510640

Abstract: The self-propelled particle models are improved by cellular automaton;through this model the peer?production system producers’?decision-making?factors are further analysed in three cases of low density space,medium?density?space,and?high-density?space.The studies show that in medium density space,the decision-making?producers’ decision mutations are?associated?not only with?the density of?the producer,but also?related with the openness of?the system?and?update intelligent?speed of?the particles?closely.Complex network model is used to improve self-propelled particle model.The results?show that when the?external influence?is small,the group?consensus?decision-making?is not affected by the network topology;in the system?stable state the?groups consensus decision-making direction is associated?with?the external initial conditions;when?external influence is larger,if external influence?and network?topology follow a certain relationship,?the results of system?groups decision-making are similar to promote?particles in?cellular automata.According to the peer production system’s scale-free?network?characteristics,the stable results are analysed in the dynamic?growth?scale-free?network,and it shows that when?the dynamically?growing?network?follows the γ>3 law,the groups behavior in the network still?has a?sudden change in the direction of?selection?in nature.

Key words: peer production system, group behaviors, complex network, self-propelled particle models, cellular automaton

摘要: 采用原胞自动机对自推动粒子模型进行改进,分析了在低密度空间、中等密度空间以及高密度空间3种情况下,大众生产系统生产者的决策影响因素。研究表明,在中等密度空间,大众生产系统中生产者的决策突变不仅与生产者的密度相关,还与系统的开放性以及智能粒子的更新速度密切相关。进一步地采用复杂网络对自推动粒子模型进行改进。结果表明,当外部影响较小时,网络拓扑结构对群体一致决策无太大影响,系统稳定时群体的一致决策方向与外部初始条件相关;当外部影响较大时,在满足外部影响与网络拓扑结构一定关系的条件下,系统中自推动粒子的群体决策与基于原胞自动机的结果相似。根据大众生产合作网络的无标度特性分析了在动态增长无标度网络中的稳定结果,得出当γ>3时动态增长的网络系统中自推动粒子的群体行为选择仍然具备突然改变方向的性质。

关键词: 大众生产系统, 群体行为, 复杂网络, 自推动粒子模型, 原胞自动机