Studies On The Dynamics Of Knowledge Communication Based On Complex Networks

This paper focuses on the studies on the Dynamics of Knowledge Communication (DKM) based on complex networks. With the paradigms of mathematic models and simulations by computer, it discusses some classical theories on Knowledge Communication (KC) with two sights: Dynamics of Structure in macro analysis and Dynamics of Behavior in micro analysis.In details, this paper achieves some results in the following aspects:1) Studies on Dynamics of Structure of KC in macro analysis. This paper proves that the characteristic parameters appears in the common KC networks according to the models of complex networks, such as the WS model, the NW model and the BA model. In this way, the studies build the Structural Model of KC based on complex networks, and obtain the power law by the simulation analysis.2) Studies on Dynamics of Behavior of KC in micro analysis. According the two kinds of behaviors including pull and push, the paper corrects the behavioral rules in Cowan Models (2004, 2006), and builds a new model on Dynamics of Behavior of KC based on complex networks with some comparative simulation results. After that, as the test of the model, a "Three-Jump" conceptual model on the KC networks is summarized and simulated with some good results to support the theoretical hypotheses.3) In order to fit the real situation, some further studies on the practice of KC management are developed by the above theoretical analyses. This paper discusses the complexity of KC based on CAS (complex adaptive systems), focuses on the Insight Leaning psychology in Chinese culture by the discrete knowledge, and builds the Q-Learning (Quantum Learning) Model to improve the Nonaka's SECI model as Q-SECI model, which is better for companies in some experiments. In the end of this paper, the author creates some new practical methods, including adding several random links in the organizations, building "Communities of Practice" in media management, and so on, to improve the Dynamics of KC based on complex networks, which has some value for KC in theory and practice in the future.