A Prototype Architecture for an Automated Scenario Generation System for Combat Simulations

Abstract

This research effort examines the problem of automating the scenario generation process and presents a prototype architecture for an automated scenario generation system. This architecture is designed using an object- oriented approach which leads to a modular and modifiable design. The architecture provides a mechanism for automatically generating scenario files from a textual US Army operation order. This translation process occurs in two phases. First, the text operation order is translated into an intermediate format called the mission file. In the second phase, the system reads the mission file, instantiates intelligent entities, and assigns missions to those entities. The intelligent entities emulate the subordinate leaders in planning missions. The thesis effort assumes that sufficiently sophisticated natural language processing algorithms can translate the operation order into the mission file. A prototype scenario generation system was implemented using NASA's CLIPS expert system development tool. The prototype system successfully translates mission files into scenario files for the BATTLESIM combat simulation model developed at the Air Force Institute of Technology.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1993
Accession Number
ADA274133

Entities

People

  • Mark W. Pfefferman

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Autonomy
  • Biomedical
  • Materials and Manufacturing Processes
  • Sensors
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Army
  • Artificial Intelligence Software
  • Computational Science
  • Computer Languages
  • Computer Programming
  • Computer Programs
  • Computers
  • Databases
  • Doctrine
  • Expert Systems
  • Geographic Regions
  • Language
  • Military Operations
  • Natural Language Processing
  • Natural Languages
  • Training
  • Warfare

Fields of Study

  • Computer science
  • Engineering

Readers

  • Parallel and Distributed Computing.
  • Software Engineering.
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - DoD AI Strategy