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Integrating Intelligent Systems into Human Teams
For this MURI project we have conducted multidisciplinary research aimed at incorporating
intelligent assistants into human teams to increase the
effectiveness of team
decision making in joint planning tasks.
The research paradigm of coordination based on developing and
maintaining shared mental models provides a common perspective
linking the intelligent agents research at Carnegie Mellon University,
the research in multi-media information delivery of the Software Engineering
Institute,
the team performance studies at the Naval Air Warfare
Training Systems Division, and
the task directed orientation to cognitive modeling and information
presentation of the University of Pittsburgh and the NRL.
To aid in the fast paced, multi user
environment of joint mission planning, assistants
develop capacities
for anticipating the information needs
of their human collaborators, preparing and communicating task
information, adapting to changes in situation and capabilities of other team
members, and effectively supporting team member mobility.
In developing adaptive and
self organizing collections of Intelligent Agents who possess models
for discriminating and communicating situational distinctions salient to
humans and to a team's mission, we have addressed the issues in incorporating
intelligent assistants into human teams. We have developed agent and system architectural principles and reusable intelligent agent software components enabling
(1) seamless integration of information access with user-centered
problem solving and decision support, (2)
active monitoring and intelligent caching of
environmental information so that users or user-delegated
intelligent assistants can acquire up-to-date situation evaluation and
therefore increase the relevance and quality of decision making, and (3)
adaptive formation of working teams among intelligent assistants
``on-demand'' depending on the information requirements of a particular task.
Our research
(1) provides a methodology for cognitive modeling of member and team tasks,
(2) provides principles for developing and supporting high performance teams,
(3) contributes to the understanding
of agent roles and human agent interactions in teams composed of humans and
intelligent agents,
(4) produces a set of architectural principles and techniques that
allow agents to cooperatively inter-operate to
provide integrated and adaptable information access, integration
and decision support,
(5) results in a set of reusable agent structuring components that
will allow system developers to rapidly construct new agents for different
end-user applications, and (6) provides techniques and tools for creating,
visually representing
and accessing large scale multimedia, multimodal information including
structured data as well as speech, text, images and video.
Our findings have
implications for other types of
planning teams that are comprised of multi-disciplinary experts. Examples
include civilian emergency response, management, and single
service military teams.
Multidisciplinary University Research Initiative (MURI) Principal Investigator: Katia Sycara
Sponsored by: Office of Naval Research (ONR)
ONR Contact: Michael Shneier
© 1998 Carnegie Mellon Robotics Institute
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