Simulating Network Behavioral Dynamics by using a Multi-agent approach driven by ACT-R Cognitive Architecture

Network Science has reported a considerable amount of human-subject experiments on which individuals have to carry out different kind of coordination games such as coloring and consensus problems in order to observe the behavioral dynamics behind the decision-making process. We have focused on the experiments carried out by Kearns (Kearns, 2010) on which were found strong correlations between the influence and other features of individual and social behavior during the execution of both kind of experiments (the coloring and consensus problems). The aim of this paper is to identify the computational underpinnings of social network behavioral through computational agent modeling using a constrained cognitive architecture framework. Final results demonstrate a strong similarity between human and model dynamics that reflects how complex network behavior can emerge from simple cognitive agents.