The Analysis of Shooting Problems via Generalised Bandits

Abstract

A single Red wishes to shoot at a collection of Blue targets in order to maximize some measure of return obtained from Blues killed before Red's own demise. While the class of decision processes called multi-armed bandits has been previously deployed to develop optimal policies for Red, we argue the importance of a little known, but more general class of bandit processes introduced by Nash (1980). In particular, the deployment of this class of processes will enable Red to take account in a natural way of the relative threats posed to his own survival in taking targeting actions. We develop optimal shooting policies for Red in the context of a range of models, which are of independent interest. The paper concludes with a numerical study.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2004
Accession Number
ADA424812

Entities

People

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

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • C4I
  • Materials and Manufacturing Processes
  • Sensors
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Defense
  • Algorithms
  • Computations
  • Deployment
  • Experimental Design
  • Mathematics
  • Military Research
  • Models
  • Operations Research
  • Probability
  • Random Variables
  • Schools
  • Statistics
  • Survival
  • Targeting
  • Targets
  • Technical Information Centers

Fields of Study

  • Computer science

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Game Theory.
  • Military History of the United States in the 20th Century.