Dynamic-probabilistic particle swarm synergetic model: A new framework for a more in-depth understanding of particle swarm algorithms

There always exists a phenomenon in human society that elitists lead certain progressive force and under their leadship, the whole multitude will go to some structure. So this paper presents a novel dynamic-probabilistic particle swarm algorithm by using mind on Synergetics developed by H. Haken. In this model we discuss how to produce the particles having the global optimal or the local optimal, how to propagate these particles´ influences and how the whole particle swarm constructs its structure. This model is a relatively complicated PSO variant that seems to be important for us to better understand the emergence and the creative process. Indepth theoretical analysis of this model is provided. Besides the probability evolution of the swarm structure is studied with the use of the stochastic difference equations. Especially, it provides a novel framework for extending the idea of particle swarm algorithms to social realm.