Transforming Intelligence: Improving Inference Through Advanced Simulations. Better Prediction Through Better Inquiry

Abstract

Recent enhancements in modeling and simulation techniques offer significant improvements for intelligence analysts to increase their inference and prediction skills. Architectural and programming improvements in techniques known as agent-based models offer analysts opportunities to increase their capabilities to deal with complex masses of evidence. These models demonstrate how the process of discovery may be improved through empowering information observations that compose evidence to interact with each other and with the analyst to drive toward more meaningful lines of inquiry - to increase the likelihood of asking more important questions in situations traditionally thought of as complex and opaque. Biologically inspired models of self-organization motivate the construction of forms of agent-based models that encourage analysts to interact more directly with the evidence they observe and to improve inference and inquiry, as well as prediction.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2003
Accession Number
ADA441749

Entities

People

  • Carl W. Hunt

Organizations

  • National War College

Tags

Communities of Interest

  • Autonomy
  • C4I
  • Human Systems

DTIC Thesaurus Topics

  • Agent-Based Simulations
  • Command And Control
  • Complex Systems
  • Computers
  • Databases
  • Information Systems
  • Intelligence Analysts
  • Intelligence Community
  • Law
  • National Security
  • New York
  • Nonlinear Dynamics
  • Phase Transformations
  • Reasoning
  • Simulations
  • United States
  • War Colleges

Readers

  • Economics
  • Educational Psychology
  • Neural Network Machine Learning.

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy