StateSim: lessons learned from 20 years of a country modeling and simulation toolset

Barry G. Silverman, Daniel M. Silverman, Gnana Bharathy, Nathan Weyer, William R. Tam

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

A holy grail for military, diplomatic, and intelligence analysis is a valid set of software agent models that act as the desired ethno-political factions so that one can test the effects of alternative courses of action in different countries. This article explains StateSim, a country modeling approach that synthesizes best-of-breed theories from across the social sciences and that has helped numerous organizations over 20 years to study insurgents, gray zone actors, and other societal instabilities. The country modeling literature is summarized (Sect. 1.1) and synthetic inquiry is contrasted with scientific inquiry (Sects. 1.2 and 2). Section 2 also explains many fielded StateSim applications and 100s of past acceptability tests and validity assessments. Section 3 then describes how users now construct and run ‘first pass’ country models within hours due to the StateSim Generator, while Sect. 4 offers two country analyses that illustrate this approach. The conclusions explain lessons learned.

Original languageEnglish (US)
Pages (from-to)231-263
Number of pages33
JournalComputational and Mathematical Organization Theory
Volume27
Issue number3
DOIs
StatePublished - Sep 2021
Externally publishedYes

Keywords

  • Cognitive agents
  • Country modeling
  • Policy analysis tools
  • Sociological game theory
  • Systems approach

ASJC Scopus subject areas

  • General Decision Sciences
  • General Computer Science
  • Modeling and Simulation
  • Computational Mathematics
  • Applied Mathematics

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