Applications of flocking algorithms to input modeling for agent movement
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Authors
Singham, Dashi
Therkildsen, Meredith
Schruben, Lee
Subjects
Advisors
Date of Issue
2011
Date
Publisher
Language
en_US
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.
Type
Conference Paper
Description
Refereed Conference Paper
The article of record as published can be found at http://dx.doi.org/10.1109/WSC.2011.6147953
The article of record as published can be found at http://dx.doi.org/10.1109/WSC.2011.6147953
Series/Report No
Department
Operations Research (OR)
Organization
Naval Postgraduate School (U.S.)
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Citation
D.Singham, M. Therkildsen, L. Schruben, "Applications of flocking algorithms to input modeling for agent movement," Proceedings of the 2011 Winter Simulation Conference, 8 p.
Distribution Statement
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This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.