Mission Plan Recognition: Developing Smart Automated Opposing Forces for Battlefield Simulations and Intelligence Analyses

Abstract

A key challenge for battlefield simulation is the estimation of enemy courses of action (COAs). Current adversarial COA development is a manual time-consuming process prone to errors due to limited knowledge about the adversary and its ability to adapt. Development of decision aids that can predict adversary's intent and range of possible behaviors, as well as automation of such technologies within battlefield simulations, would greatly enhance the efficacy of training and mission rehearsal solutions. In this paper, we describe the development of OPFOR agents that can intelligently learn BLUEFOR's mission plan. This knowledge will allow OPFOR agent to reason about the intent of BLUE and counteract accordingly to prevent/influence the future BLUEFOR's operations by affecting current operations, challenging BLUE's resources, and preparing OPFOR for future battles.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2008
Accession Number
ADA486796

Entities

People

  • Alexander Kott
  • Darby Grande
  • Georgiy M. Levchuk
  • Krishna R. Pattipati
  • Yuri Levchuk

Organizations

  • Aptima (United States)

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies
  • Materials and Manufacturing Processes
  • Weapons Technologies

DTIC Thesaurus Topics

  • Agent-Based Simulations
  • Algorithms
  • Artificial Intelligence
  • Battlefields
  • Command And Control
  • Computational Science
  • Electronic Mail
  • Identification
  • Intelligence Analysis
  • Machine Learning
  • Mathematical Models
  • Military Organizations
  • Organizational Structure
  • Probability
  • Recognition
  • Simulations
  • Training

Fields of Study

  • Computer science

Readers

  • Game Theory.
  • Military Training and Readiness Simulation
  • Systems Analysis and Design