The synthetic teammate project

Jerry Ball, Christopher Myers, Andrea Heiberg, Nancy J. Cooke, Michael Matessa, Mary Freiman, Stuart Rodgers

Research output: Contribution to journalArticlepeer-review

57 Scopus citations


The main objective of the Synthetic Teammate project is to develop language and task enabled synthetic agents capable of being integrated into team training simulations. To achieve this goal, the agents must be able to closely match human behavior. The initial application for the synthetic teammate research is creation of an agent able to perform the functions of a pilot for an Unmanned Aerial Vehicle (UAV) simulation as part of a three-person team. The agent, or synthetic teammate, is being developed in the ACT-R cognitive architecture. The major components include: language comprehension and generation, dialog management, agent-environment interaction, and situation assessment. Initial empirical results suggest that the agent-environment interaction is a good approximation to human behavior in the UAV environment, and we are planning further empirical tests of the synthetic teammate operating with human teammates. This paper covers the project's modeling approach, challenges faced, progress made toward an integrated synthetic teammate, and lessons learned during development.

Original languageEnglish (US)
Pages (from-to)271-299
Number of pages29
JournalComputational and Mathematical Organization Theory
Issue number3
StatePublished - 2010
Externally publishedYes


  • Agent-environment interaction
  • Dialog management
  • Language comprehension/generation
  • Situation model
  • Synthetic teammate

ASJC Scopus subject areas

  • General Decision Sciences
  • General Computer Science
  • Modeling and Simulation
  • Computational Mathematics
  • Applied Mathematics


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