Citation

Zou Y, Fonoberov VA, Fonoberova M, Mezic I, Kevrekidis IG. Phys. Rev. E Stat. Nonlin. Soft Matter Phys. 2012; 85(6).

Copyright

(Copyright © 2012, American Physical Society, Publisher American Institute of Physics)

DOI

10.1103/PhysRevE.85.066106

PMID

unavailable

Abstract

Agent-based modeling (ABM) constitutes a powerful computational tool for the exploration of phenomena involving emergent dynamic behavior in the social sciences. This paper demonstrates a computer-assisted approach that bridges the significant gap between the single-agent microscopic level and the macroscopic (coarse-grained population) level, where fundamental questions must be rationally answered and policies guiding the emergent dynamics devised. Our approach will be illustrated through an agent-based model of civil violence. This spatiotemporally varying ABM incorporates interactions between a heterogeneous population of citizens [active (insurgent), inactive, or jailed] and a population of police officers. Detailed simulations exhibit an equilibrium punctuated by periods of social upheavals. We show how to effectively reduce the agent-based dynamics to a stochastic model with only two coarse-grained degrees of freedom: the number of jailed citizens and the number of active ones. The coarse-grained model captures the ABM dynamics while drastically reducing the computation time (by a factor of approximately 20). 2012 American Physical Society.