@article{ref1,
title="Model reduction for agent-based social simulation: Coarse-graining a civil violence model",
journal="Physical review E: Statistical, nonlinear, and soft matter physics",
year="2012",
author="Zou, Yu and Fonoberov, Vladimir A. and Fonoberova, Maria and Mezic, Igor and Kevrekidis, Ioannis G.",
volume="85",
number="6-2",
pages="066106-066106",
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).<p /> <p>Language: en</p>",
language="en",
issn="1539-3755",
doi="",
url="http://dx.doi.org/"
}