Developing an Effective and Efficient Real Time Strategy Agent for Use as a Computer Generated Force

Abstract

Computer Generated Forces (CGF) are used as units or people in military training and simulation. The use of CGF significantly reduces the time and money required for effective training. Real Time Strategy (RTS) games place players in control of a large force whose goal is to defeat the opponent. The military setting of RTS games makes them an excellent platform for the development and testing of CGF. While significant research has been done into RTS agent development, most of the developed agents are only able to exhibit good tactical behavior. By analyzing prior games played by an opposing agent, an RTS agent could determine the opponent's strengths and weaknesses and develop a strategy which neutralizes the strengths and capitalizes on the weaknesses. It could then execute this strategy in an RTS game. This research develops the Killer Bee Artificial Intelligence (KBAI). KBAI takes a classifier for the RTS domain, uses it to generate an effective counter-strategy, and executes the tactics required for the strategy.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2010
Accession Number
ADA516703

Entities

People

  • Kurt Weissgerber

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Autonomy
  • Energy and Power Technologies
  • Human Systems

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Artificial Intelligence
  • Bayesian Networks
  • Computational Science
  • Computer Programming
  • Computer Programs
  • Computers
  • Energy Production
  • Evolutionary Algorithms
  • Genetic Algorithms
  • Machine Learning
  • Military Operations
  • Military Training
  • Operating Systems
  • Particle Swarm Optimization
  • Warfare

Readers

  • Data Mining and Knowledge Discovery.
  • Joint Military Operations and Doctrine.
  • Political Violence and Terrorism Studies.

Technology Areas

  • AI & ML