Representing and Solving Air Campaign Problems as Partially Observable Markov Decision Problems

Abstract

The original purpose of this project was to design algorithms and architectures for maintenance and deployment scheduling solutions to support large-scale strategic military airlift activities related to the needs of the Air Mobility Command (AMC), and secondarily to adapt these solutions to other military and civilian planning and scheduling problems. The research adopted a stochastic modeling framework and used novel techniques for planning in unpredictable dynamic environments with complex state and action spaces. Many of the original goals of the project were achieved in conjunction with the primary contract; however, several extensions were carried out by students receiving funding from the AASERT supplementary grant.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jun 30, 2001
Accession Number
ADA395052

Entities

People

  • Thomas L. Dean

Organizations

  • Brown University

Tags

Communities of Interest

  • C4I
  • Human Systems
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Automata Theory
  • Bayesian Networks
  • Computational Science
  • Computer Programming
  • Computer Science
  • Linear Programming
  • Mathematical Models
  • Monte Carlo Method
  • Operating Systems
  • Operations Research
  • Optimization
  • Probabilistic Models
  • Probability
  • Probability Distributions
  • Random Variables

Readers

  • Aerospace logistics and air mobility.
  • Operations Research
  • Systems Analysis and Design

Technology Areas

  • Space