Agent-Based Simulation and Sociological Understanding

Abstract

The article discusses agent-based simulation as a tool of sociological understanding. Based on an inferential account of understanding, it argues that computer simulations increase our explanatory understanding both by expanding our ability to make what-if inferences about social processes and by making these inferences more reliable. However, our ability to understand simulations limits our ability to understand real world phenomena through them. Thomas Schelling's checkerboard model of ethnic segregation is used to demonstrate the important role played by abstract how-possibly models in the process of building a mechanistic understanding of social phenomena.