Military Stochastic Scheduling Treated As a 'Multi-Armed Bandit' Problem

Abstract

A Blue airborne force attacks a region defended by a single Red surface-to-air missile system (SAM). Red is uncertain about the Blues he faces, but is able to learn about them during the engagement. Red's objective is to develop a policy for shooting at the Blues to maximize the value of Blues shot down before he himself is destroyed. We show that index policies are optimal for Red in a range of scenarios and yield effective heuristics more generally. The quality of such index heuristics is confirmed in a computational study.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2001
Accession Number
ADA395044

Entities

People

  • Donald P. Gaver Jr.
  • Kevin D. Glazebrook
  • Patricia A. Jacobs

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Sensors
  • Weapons Technologies

DTIC Thesaurus Topics

  • Abstracts
  • Air Defense
  • Bayesian Networks
  • Experimental Design
  • Models
  • Operations Research
  • Probability
  • Random Variables
  • Scheduling (Production)
  • Schools
  • Simulations
  • Statistics
  • Systems Science
  • Targets
  • Technical Information Centers
  • Test And Evaluation
  • Virtual Reality

Readers

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  • Immunology
  • Sensor Fusion and Tracking Systems.