Enhancing Simulation-based Training Adversary Tactics via Evolution (ESTATE)

Abstract

To extend modern simulation-based training environments to incorporate tailored simulation-based training experiences to facilitate accelerated skills development and sustainment, we are developing a system for Enhancing Simulation-based Training Adversary Tactics via Evolution (ESTATE). The system consists of an off-line adaptation engine to extract a model of the trainee based on past performance and generate tailored challenge problems for on-line training. Off-line adaptation is performed using evolutionary algorithms (EAs) to search through the space of challenges to exploit fundamental weaknesses in trainee strategy and tactics. The full-scope prototype ESTATE system is targeting simulation-based training systems within the Deployable Virtual Training Environment (DVTE) to support the squad-level training of U.S. Marines. This report documents the Option 1 period of the effort.

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Document Details

Document Type
Technical Report
Publication Date
Dec 15, 2010
Accession Number
ADA534778

Entities

People

  • Bjorn Gunnarsson
  • Brad R Rosenberg
  • James Niehaus
  • Jordan Pollack
  • Max Metzger
  • Scott N. Reilly

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Adaptive Training
  • Algorithms
  • Computer Science
  • Computers
  • Disaster Management
  • Education
  • Environment
  • Evolutionary Algorithms
  • First Aid
  • Game Theory
  • Health Services
  • Medical Personnel
  • Models
  • Simulations
  • Students
  • Trainees
  • Training

Fields of Study

  • Computer science

Readers

  • Distributed Systems and Data Platform Development
  • Enterprise Information Systems Architecture and Joint Command Capability Interoperability Support.
  • Military Training and Readiness Simulation

Technology Areas

  • Space