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Disasters, whether natural or human-made, may strike at any time. The better prepared emergency crews and public officials are, the more successful their responses will be. Writing for Science magazine, Mitchell Waldrop explains how a new digital simulation technique – agent-based modeling – is helping researchers and public officials anticipate disaster outcomes and tackle real-world problems with greater speed, accuracy and effectiveness. getAbstract recommends this fascinating article to public officials and anybody looking for ways to model the world’s complexity.

In this summary, you will learn

  • How agent-based models simulate real-world disasters;
  • Why agent-based models deliver superior results compared to traditional fixed-scenario simulations; and 
  • How agent-based computer simulations can help epidemiologists save lives.
 

About the Author

M. Mitchell Waldrop is a journalist based in Washington, DC.

 

Summary

Agent-based modeling is a digital technique for simulating real-world events and disaster scenarios.

National security officials used to rely on fixed scenarios when devising disaster response plans. Today, they increasingly deploy agent-based models, which simulate the actions and interactions of individuals. These simulations capture emerging outcomes from the bottom up, leading to more realistic and flexible predictive models and what-if scenarios. In addition, the models take many variables into account that might affect the outcome, such as weather patterns or the location of hospitals and cell phone towers. In the US government’s National Planning Scenario 1, which simulates a nuclear attack on the capital, agent-based modeling has helped officials identify potential traffic bottlenecks and study the impact of quickly restoring cell phone communication on people’s behavior.


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