An agent-based microsimulation of critical infrastructure systems

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US infrastructures provide essential services that support the economic prosperity and quality of life. Today, the latest threat to these infrastructures is the increasing complexity and interconnectedness of the system. On balance, added connectivity will improve economic efficiency; however, increased coupling could also result in situations where a disturbance in an isolated infrastructure unexpectedly cascades across diverse infrastructures. An understanding of the behavior of complex systems can be critical to understanding and predicting infrastructure responses to unexpected perturbation. Sandia National Laboratories has developed an agent-based model of critical US infrastructures using time-dependent Monte Carlo methods and a genetic algorithm learning ... continued below

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6 p.

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BARTON,DIANNE C. & STAMBER,KEVIN L. March 29, 2000.

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This article is part of the collection entitled: Office of Scientific & Technical Information Technical Reports and was provided by UNT Libraries Government Documents Department to Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 17 times . More information about this article can be viewed below.

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  • Sandia National Laboratories
    Publisher Info: Sandia National Labs., Albuquerque, NM, and Livermore, CA
    Place of Publication: Albuquerque, New Mexico

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Description

US infrastructures provide essential services that support the economic prosperity and quality of life. Today, the latest threat to these infrastructures is the increasing complexity and interconnectedness of the system. On balance, added connectivity will improve economic efficiency; however, increased coupling could also result in situations where a disturbance in an isolated infrastructure unexpectedly cascades across diverse infrastructures. An understanding of the behavior of complex systems can be critical to understanding and predicting infrastructure responses to unexpected perturbation. Sandia National Laboratories has developed an agent-based model of critical US infrastructures using time-dependent Monte Carlo methods and a genetic algorithm learning classifier system to control decision making. The model is currently under development and contains agents that represent the several areas within the interconnected infrastructures, including electric power and fuel supply. Previous work shows that agent-based simulations models have the potential to improve the accuracy of complex system forecasting and to provide new insights into the factors that are the primary drivers of emergent behaviors in interdependent systems. Simulation results can be examined both computationally and analytically, offering new ways of theorizing about the impact of perturbations to an infrastructure network.

Physical Description

6 p.

Notes

OSTI as DE00753426

Medium: P; Size: 6 pages

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  • International Energy Foundation's ENERGEX 2000 - 8th International Energy Forum, Las Vegas, NV (US), 07/23/2000--07/28/2000

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  • Report No.: SAND2000-0808C
  • Grant Number: AC04-94AL85000
  • Office of Scientific & Technical Information Report Number: 753426
  • Archival Resource Key: ark:/67531/metadc706063

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Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

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  • March 29, 2000

Added to The UNT Digital Library

  • Sept. 12, 2015, 6:31 a.m.

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  • April 11, 2017, 12:55 p.m.

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BARTON,DIANNE C. & STAMBER,KEVIN L. An agent-based microsimulation of critical infrastructure systems, article, March 29, 2000; Albuquerque, New Mexico. (digital.library.unt.edu/ark:/67531/metadc706063/: accessed October 22, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.