Coevolutionary Characteristics of Knowledge Diffusion and Knowledge Network Structures: A GA-ABM Model

被引：4

作者：

Jang, Junhyok ^{[1
,2
]}

Ju, Xiaofeng ^{[1
]}

Ryu, Unsok ^{[3
]}

Om, Hyonchol ^{[4
]}

机构：

[1] Harbin Inst Technol, Sch Management, 92 Xidazhi St, Harbin 150001, Heilongjiang, Peoples R China

[2] Kimchaek Univ Technol, Sch Phys Sci, Yonggwang St, Pyongyang 950003, North Korea

[3] Kim IlSung Univ, Sch Informat Sci, KumSong St, Pyongyang 999093, North Korea

[4] Kim IlSung Univ, Sch Chem, KumSong St, Pyongyang 999093, North Korea

来源：

JASSS-THE JOURNAL OF ARTIFICIAL SOCIETIES AND SOCIAL SIMULATION | 2019年 / 22卷 / 03期

基金：

美国国家科学基金会;

关键词：

Knowledge Diffusion; Knowledge Network; Coevolutionary; Genetic Algorithm; Agent-Based Modeling; DYNAMICS;

D O I：

10.18564/jasss.4037

中图分类号：

C [社会科学总论];

学科分类号：

03 ; 0303 ;

摘要：

The co-evolutionary dynamics of knowledge diffusion and network structure in knowledge management is a recent research trend in the field of complex networks. The aim of this study is to improve the knowledge diffusion performance of knowledge networks including personnel, innovative organizations and companies. In order to study the co-evolutionary dynamics of knowledge diffusion and network structure, we developed a genetic algorithm-agent based model (GA-ABM) by combining a genetic algorithm (GA) and an agent-based model (ABM). Our simulations show that our GA-ABM improved the average knowledge stock and knowledge growth rate of the whole network, compared with several other models. In addition, it was shown that the topological structure of the optimal network obtained by GA-ABM has the property of a random network. Finally, we found that the clustering coefficients of agents are not significant to improve knowledge diffusion performance.

引用

页数：17

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