Forecasting Irregular Warfare via Agent-Based Network Models
Abstract
This project aimed at modeling future trajectories of irregular warfare (IW) through multiagent social simulation. The project objectives were to use social science to understand the social and political landscapes of IW; create a high-fidelity multiagent social simulation model (LRG-AFG) of the co-evolution of insurgency and counterinsurgency (COIN), embedded in a realistic and theoretically informed model of the local social, political, and economic landscapes; build an understanding of forces in the local population that support or oppose the existence of covert networks; describe the evolution of friend-or-foe attitudes among the population, and develop a model of the political economy of insurgency. To the best of our knowledge, LRG-AFG is at the time of submission of this report the most sophisticated, open source simulation of a political economy affected by armed conflict. LRG-AFG is a simulation of rural Afghanistan with 1.5M household agents that lends itself to rigorous analytical work and robust support for decision making.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jul 15, 2011
- Accession Number
- ADA546483
Entities
People
- Anamaria Berea
- Armando Geller
- Claudio Cioffi-revilla
- Hoda Osman
- Joseph F. Harrison
- Maciej M. Latek
- Matthew Revelle
- Seyed M. Mussavi Rizi
Organizations
- George Mason University