Applications of Flocking Algorithms to Input Modeling for Agent Movement

Abstract

Simulation flocking has been introduced as a method for generating simulation input from multivariate dependent time series for sensitivity and risk analysis. It can be applied to data for which a parametric model is not readily available or imposes too many restrictions on the possible inputs. This method uses techniques from agent-based modeling to generate a flock of boids that follow the data. In this paper, we apply simulation flocking to a border crossing scenario to determine if waypoints simulated from flocking can be used to provide improved information on the number of hostiles successfully crossing the border. Analysis of the output reveals scenario limitations and potential areas of improvement in the patrol strategy.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2011
Accession Number
ADA558484

Entities

People

  • Dashi I. Singham
  • Lee Schruben
  • Meredith Therkildsen

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Weapons Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Business Administration
  • Crossings
  • Electronic Mail
  • Engineering
  • Geographic Regions
  • Industrial Engineering
  • Mathematics
  • Mountains
  • New Zealand
  • Operations Research
  • Probability
  • Random Variables
  • Risk
  • Sensitivity
  • Simulations
  • Terrain

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Computational Modeling and Simulation