Negotiation over tasks in hybrid human-agent teams for simulation-based training

  • Authors:

  • David Traum;Jeff Rickel;Jonathan Gratch;Stacy Marsella

  • Affiliations:

  • USC Institute for Creative Technologies, Marina del Rey, CA;USC Information Sciences Institute, Marina del Rey, CA;USC Institute for Creative Technologies, Marina del Rey, CA;USC Information Sciences Institute, Marina del Rey, CA

  • Venue:
  • AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
  • Year:
  • 2003

Quantified Score

Hi-index 0.00

Visualization

Abstract

The effectiveness of simulation-based training for individual tasks -- such as piloting skills -- is well established, but its use for team training raises challenging technical issues. Ideally, human users could gain valuable leadership experience by interacting with synthetic teammates in realistic and potentially stressful scenarios. However, creating human-like teammates that can support flexible, natural interactions with humans and other synthetic agents requires integrating a wide variety of capabilities, including models of teamwork, models of human negotiation, and the ability to participate in face-to-face spoken conversations in virtual worlds. We have developed such virtual humans by integrating and extending prior work in these areas, and we have applied our virtual humans to an example peacekeeping training scenario to guide and evaluate our research. Our models allow agents to reason about authority and responsibility for individual actions in a team task and, as appropriate, to carry out actions, give and accept orders, monitor task execution, and negotiate options. Negotiation is guided by the agents' dynamic assessment of alternative actions given the current scenario conditions, with the aim of guiding the human user towards an ability to make similar assessments.