Ants on the AEDGE: Adding Personality to Swarm Intelligence


Predicting motion of a target will forever be an elusive goal to targeting system operators. The problem is made even more difficult when there is an intelligence that is actively attempting to elude detection. The intelligence that is tracked in this article is that of a Mobile Missile Launcher (MML) actively attempting to avoid detection and subsequent destruction by cruise missiles. The approach taken is to track the MML using swarm intelligence combined with personality traits of human operators to predict the most likely locations the MML may be. The tracking is augmented by allowing the user to interact with the swarm agents to help guide the tracking algorithm using a mathematical concept known as belief algebra. Preliminary results are shown that the swarm predicts the most likely location of simulated target. This work was initially started under a Small Business Innovative Research award to 21st Century Systems, Inc. (21CSI).

  • Abstract
  • 1.0 Introduction
  • 2.0 Predicting Human Action
  • 2.1. Ants on the Aedge (AoA) Ant Agent Analysis
  • 2.2. Belief Fusion
  • 2.3. Demonstration Results
  • 3.0 Conclusions
  • References

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