Swarm Observations: Implementing Integration Theory to Understand an Opponent Swarm

Abstract

Swarm counter measure systems currently use enhanced weapons and sensor capabilities to address the threat of opponent swarms. However, there is a gap in current defense capabilities to counter swarm attacks, because brute force, or the enhancement of current defense systems by adding to defense capabilities are inadequate because of the inherent robustness, flexibility and adaptation of swarm attacks. Because of this, an overarching model is sought to understand the underlying command and control mechanism of an observed swarm threat, so that mechanisms that determine swarm behaviors can be understood. This will enable the development of countermeasures to counter swarms using specialized systems or tactics for certain behavior types. Integration theory provides an abstract model adequate throughout disparate swarm intelligence-domains (such as biology, computer algorithms, physics, and sociology). Integration theory, used with agent based modeling and analytical methods such as fractal dimensions, entropy, correlation and spatiotemporal structures, shows that it is possible to differentiate among the underlying C2 mechanisms by observing the swarm movement patterns. Adopting a swarm analytical observation approach is advised to promote the implementation of effective future countermeasures.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2012
Accession Number
ADA567354

Entities

People

  • Anner G. Diukman

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Autonomy
  • Biomedical
  • C4I
  • Ground and Sea Platforms
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Agent-Based Simulations
  • Algorithms
  • Chemical Reactions
  • Cognitive Systems Engineering
  • Command And Control
  • Computational Science
  • Control Systems
  • Defense Systems
  • Human Systems Integration
  • Particle Swarm Optimization
  • Self Organizing Systems
  • Social Sciences
  • Swarm Intelligence
  • Systems Engineering
  • Unmanned Aerial Vehicles
  • Unmanned Systems
  • Unmanned Vehicles

Fields of Study

  • Computer science

Readers

  • Theoretical Analysis.
  • Unmanned Aerial System (UAS) Autonomous Capabilities and Mission Reconnaissance.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - DoD AI Strategy
  • Autonomy
  • Autonomy - Autonomous System Control
  • Fully Networked C3
  • Fully Networked C3 - Command and Control