A future framework for interfacing BDI agents in a real-time teaming environment

  • Authors:

  • Pierre Urlings;Christos Sioutis;Jeff Tweedale;Nikhil Ichalkaranje;Lakhmi Jain

  • Affiliations:

  • Airborne Mission Systems, Australian Defence Science and Technology Organisation, Australia;School of Electrical and Information Engineering, University of South Australia, Australia;Airborne Mission Systems, Australian Defence Science and Technology Organisation, Australia;School of Electrical and Information Engineering, University of South Australia, Australia;School of Electrical and Information Engineering, University of South Australia, Australia

  • Venue:
  • Journal of Network and Computer Applications - Special issue: Innovations in agent collaboration
  • Year:
  • 2006

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Abstract

Research and applications in human-machine teaming continue to evolve the role of the human from immediate (manual) operator into supervisory and televisory controller. In the supervisory control role, the human operator will be functionally removed from the system under control and in the televisory role, the human operator will be physically removed. Although unmanned systems and vehicles have become a technical reality that drives this change, they will not eliminate the importance of the human operator as the commanding and controlling element in-the-loop. This paper will argue that existing automation concepts remain equally valid with an even greater emphasis on the need for a human-centered automation approach. Intelligent agent technology has become mature and attractive enough to implement the automated components of the human-machine team. Agents that implement the Beliefs-Desire-Intention syntax will be discussed as being of particular interest for human-machine teaming applications. This paper proposes a theoretical framework for teaming human and intelligent agents. The teaming framework will be demonstrated in a real-time simulation environment using the commercial game called Unreal Tournament and its existing GameBot extension. The intelligent agents will be implemented based on the Belief-Desire-Intention (BDI) syntax and using JACK, a commercial BDI Agent development language. The requirements for follow-on research, such as human-agent teaming, human-agent coordination and agent learning will be highlighted.