Model Acquisition for Markov Decision Problems

Abstract

The original focus of this work was on the automatic acquisition (learning) of stochastic models. The motivation was the lack of such models for military problems, specifically air-campaign planning, and the existence of new algorithms that could, if the appropriate models were available, considerably improve the accuracy and efficiency of military planning. This final report describes the course of our investigations, some unanticipated turns, and the direction that our research has taken as a consequence of what we have learned.

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Document Details

Document Type
Technical Report
Publication Date
Oct 31, 1998
Accession Number
ADA380049

Entities

People

  • Thomas Dean

Organizations

  • Brown University

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Acquisition
  • Air Force
  • Algorithms
  • Artificial Intelligence
  • Causal Reasoning
  • Computations
  • Computer Science
  • Dynamics
  • Hidden Markov Models
  • Information Processing
  • Learning
  • Markov Models
  • Military Planning
  • Models
  • Reasoning
  • Scientific Research
  • Stochastic Processes

Readers

  • Artificial Intelligence
  • Computational Modeling and Simulation
  • Operations Research