A Theoretic Analysis of Combined Arms Teaming

Abstract

This study presents a foundation for the comparative analysis of the various combined arms teaming in a simulated environment. The study consists of three stages. First, a discrete-event combat-simulation model of two opposing generic combined arms teams is developed. This model is used to study the relationships between six key attributes of combined arms teams: communication; detection; lethality; mobility; protection; and sustainment. Second, a genetic algorithm is embedded within the combat-simulator to evolve strategies for combined arms teams against a static opposing force. Finally, a two-population genetic algorithm is used to coevolve two opposing forces against each other. Games theory is used to analyze the results and to provide advice on the impact of adding, removing and replacing assets or capabilities within the teams. We conclude that diversity and specialization within combined arms teams is essential to the Land force. Furthermore, no single combined arms team is sufficient to ensure a tactical victory on the battlefield against all potential opponents. A range of different options for constructing combined arms teams is required.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2005
Accession Number
ADA437869

Entities

People

  • Scott Wheeler

Tags

Communities of Interest

  • Autonomy
  • C4I
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Applied Mathematics
  • Combat Simulations
  • Computational Science
  • Computer Science
  • Computer Simulations
  • Evolutionary Algorithms
  • Game Theory
  • Genetic Algorithms
  • Mathematical Programming
  • Operations Research
  • Optimization
  • Random Variables
  • Situational Awareness
  • Stochastic Processes
  • Warfare
  • Weapons

Fields of Study

  • Engineering

Readers

  • Computational Modeling and Simulation
  • Military Training and Readiness Simulation
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.

Technology Areas

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