Cognitively Based Modeling of Scientific Productivity

Abstract

This chapter advocates a cognitively realistic approach to social simulation. based on a model for capturing the growth of academic science. Gilbert’s (1997) model, which was equation based, is replaced in this work by an agent-based model, with the cognitive architecture CLARION providing greater cognitive realism. Using this agent model, results comparable to human data are obtained. It is found that while different cognitive settings may affect aggregate productivity of scientific articles, generally they do not lead to different distributions of productivity. It is argued that using more cognitively realistic models in social simulations may lead to novel insights.