Learning Networks: Iran and the Effects of Sanctions

Abstract

Iranian government, financial, and business entities are adapting to, and learning from, each new round of international sanctions. When a sanction is imposed, agents and organizations, predictably, develop creative methods to bypass it in order to continue the pursuit of nuclear weapons production. Based on this scenario, can we quantitatively model the evolution and learning of this Iranian Network? This was the question posed to three summer apprentices at the Network Science Center over the course of their internship during the summer of 2012. Based on team discussions, the group developed three possible methods to formulate and analyze this issue. These network-based techniques are introduced: standard network analysis, time series analysis, and network flows. This paper synthesizes and summarizes our research efforts.

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Document Details

Document Type
Technical Report
Publication Date
Mar 27, 2013
Accession Number
ADA582400

Entities

People

  • Daniel Evans
  • Lauren Kewley
  • Louis Boguchwal
  • Marc A. Johnson

Organizations

  • United States Military Academy

Tags

Communities of Interest

  • Counter WMD
  • Energy and Power Technologies
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Commerce
  • Department Of Defense
  • European Union
  • Governments
  • Internal Pressure
  • Learning
  • Military Organizations
  • Military Research
  • Network Science
  • Nuclear Weapons
  • Production
  • Standards
  • Time Series Analysis
  • United States
  • United States Military Academy
  • Weapons

Fields of Study

  • Computer science

Readers

  • Computer Networking
  • Nuclear Non-Proliferation and International Security
  • Theoretical Analysis.