Decision Support for Asymmetric Urban Warfare

Abstract

The deciphering of intelligence is a complex task and if not explained clearly can cause confusion in battle, ultimately increasing the probability of fratricide and loss. Various methods have been tried to simplify the deciphering of intelligence, many of which are simplistic and deterministic in their nature (e.g. fuzzy logic). In this paper, we employ two probabilistic techniques (Bayesian Networks and Influence Diagrams), widely accepted in a variety of industries, to aid decision makers by determining the most probable outcome based on the intelligence known at the time. The methodology described in this paper relates to an asymmetric urban warfare scenario and has proven to be robust and insensitive to reasonable changes in the data. The time taken to develop and understand a Bayesian Network or Influence Diagram makes it improbable for satisfactory use within a high tempo real life scenario. These tools are potentially useful during the intelligence preparation phase and as decision support tools for areas such as troop allocation and operational planning.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2006
Accession Number
ADA474180

Entities

People

  • Ken Mcnaught
  • Tracey Enderwick

Organizations

  • Cranfield University

Tags

Communities of Interest

  • Energy and Power Technologies
  • Human Systems
  • Weapons Technologies

DTIC Thesaurus Topics

  • Abstracts
  • Army Personnel
  • Asymmetric Warfare
  • Bayesian Networks
  • Governments
  • Improvised Explosive Devices
  • Man Borne Improvised Explosive Devices
  • Models
  • Nato Forces
  • Police
  • Probability
  • Probability Distributions
  • Terrorism
  • Terrorists
  • Urban Warfare
  • Vehicle Borne Improvised Explosive Devices
  • Warfare

Readers

  • Artificial Intelligence
  • Computational Modeling and Simulation
  • Military History / Militaries and War Studies

Technology Areas

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