Automated Influence Network Generation and the Node Parameter Sensitivity Analysis

Abstract

An influence network is a directed graph extensively used for Effects-Based Operation. It contains nodes that represent events and links that encode causal relationships among events. It propagates the likelihood of each event through promotion or inhibition by its parents. As a subject matter expert often builds this network by hand, we helped simplify the influence network generation in Organization Risk Analyzer. The resulting influence network is generated from a multi-mode, multi-plex organizational network structure, and the generation scheme is based on assessing event flows and evaluating the factors on task management of the organization. To support the soundness of such network generation we provide sensitivity analysis of baseline probabilities, a major parameter of the model, by bootstrap sampling of the leaf nodes and propagating different levels of assigned parameters. Finally, we provide an example of analysis by utilizing the introduced generation method and a dataset from 1998 US embassy bombing in Kenya.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2008
Accession Number
ADA487038

Entities

People

  • Eunice J. Kim
  • Il-chul Moon
  • Kathleen Carley

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • C4I
  • Human Systems

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Command And Control
  • Computer Programs
  • Computer Science
  • Education
  • Human Resources
  • Inhibition
  • Operations Research
  • Organizational Structure
  • Probability
  • Sensitivity
  • Social Networks
  • Systems Engineering
  • Task Performance And Analysis
  • Terrorists
  • Vehicle Borne Improvised Explosive Devices
  • Visualizations

Fields of Study

  • Computer science

Readers

  • Computational Modeling and Simulation
  • Political Violence and Terrorism Studies.