Analysis of Shipboard Firefighting-Team Efficiency Using Intelligent-Agent Simulation

Abstract

Analysis of the efficiency of organizational structures is important for command-and-control since an intuitively appealing structure may have unanticipated bottlenecks that occur with unexpected events and the skill levels of personnel. Good simulation can find some of these problems, but it hard to build good simulations. So we have developed tools to enable analysts to set up discrete-event multi-agent simulations in straightforward ways without having to program. We describe here our application of these tools to shipboard firefighting, which presents difficult problems for planners. Our tools uses artificial-intelligence techniques such as means-ends analysis to simulate the actions and interactions of a fire team, and uses a stochastic model for fire spread based on the kind of flammable material, its ignition and burnout rates, and the possibility of burnout and flashover effects. The duration of an action depends on the skill level of the team member in charge of the action. To assess the readiness of teams with different combinations of skills, we measured the duration of firefighting in random trials. We showed that a good scene leader is not sufficient to assure a good performance when unskilled nozzlemen and hosemen are part of the team, and we showed that skill levels did not matter much when ignition and burnout rates were high.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2002
Accession Number
ADA458054

Entities

People

  • Donald P. Gaver Jr.
  • Neil C. Rowe
  • Patricia A. Jacobs
  • Sylvio F. Andrade

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Biomedical
  • Ground and Sea Platforms
  • Human Systems

DTIC Thesaurus Topics

  • Abstracts
  • Agent-Based Simulations
  • Artificial Intelligence
  • Chemical Reactions
  • Combustion
  • Command Centers
  • Efficiency
  • Emergencies
  • Firefighters
  • Fires
  • Ignition
  • Materials
  • Mathematical Models
  • Organizational Structure
  • Probability
  • Random Variables
  • Simulations

Readers

  • Educational Psychology
  • Fire Suppression Systems Design.
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - DoD AI Strategy
  • Fully Networked C3
  • Fully Networked C3 - Command and Control