Automated scenario generation: toward tailored and optimized military training in virtual environments

  • Authors:

  • Alexander Zook;Stephen Lee-Urban;Mark O. Riedl;Heather K. Holden;Robert A. Sottilare;Keith W. Brawner

  • Affiliations:

  • Georgia Institute of Technology, Atlanta, Georgia;Georgia Institute of Technology, Atlanta, Georgia;Georgia Institute of Technology, Atlanta, Georgia;U.S. Army Research Laboratory, Orlando, Florida;U.S. Army Research Laboratory, Orlando, Florida;U.S. Army Research Laboratory, Orlando, Florida

  • Venue:
  • Proceedings of the International Conference on the Foundations of Digital Games
  • Year:
  • 2012

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Abstract

Scenario-based training exemplifies the learning-by-doing approach to human performance improvement. In this paper, we enumerate the advantages of incorporating automated scenario generation technologies into the traditional scenario development pipeline. An automated scenario generator is a system that creates training scenarios from scratch, augmenting human authoring to rapidly develop new scenarios, providing a richer diversity of tailored training opportunities, and delivering training scenarios on demand. We introduce a combinatorial optimization approach to scenario generation to deliver the requisite diversity and quality of scenarios while tailoring the scenarios to a particular learner's needs and abilities. We propose a set of evaluation metrics appropriate to scenario generation technologies and present preliminary evidence for the suitability of our approach compared to other scenario generation approaches.