Knowledge transfer in homogeneous networks with consideration of self-learning mechanism

Depending on the fact that knowledge can be learned by oneself, which is different from epidemic spreading, we take into account self-learning mechanism in the knowledge transfer process. In this paper, we propose a knowledge transfer model, and derive the mean-field equations that describe the dynamics of the knowledge transfer in homogeneous networks. Using differential theory, we obtain the knowledge transfer threshold and solution of the mean-field equations. Both the solution and threshold are closely related with self-learning rate. In addition, numerical simulations are performed to verify the reasonability of the theoretical analysis. The results indicate that the self-learning mechanism have obvious promoting effect on the knowledge transfer in homogeneous networks.