A Szilard model-based computational study of the evolution of agents-clusters

Abstract

A theoretical model based on the cluster theory was developed and used to simulate the dynamics of complex systems, composed of a number of interacting agents-clusters, with different sizes M. The case of systems formed by a constant total number of agents in metastable (partial) equilibrium was considered, and the size effect on the formation of groups of agents (clusters) was particularly elucidated. We prove that the random evolution of groups of agents definitely depends on the size of the group. The average group (cluster) size problem was also solved for different values of M, and the process of relaxation in the system was studied. The role of attachment probability in “quantifying” economic growth is described by comparison between this model and other kinetic models of random growing networks and herding phenomena.