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a video of the Joccasta Demo
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here to go directly to our
MURI Project Page.
In
order to increase team decision making in the area of joint
mission planning, we are incorporating intelligent software
assistants into human teams. This Multidisciplinary
University Research Initiative (MURI) brings together
the Software Agents Group at Carnegie Mellon University,
the Software Engineering Institute's research on multimedia
information delivery, the Performance Studies Team at the
Naval Air Warfare Training Systems Division, the University
of Pittsburgh, and the NRL.
Software
assistants can anticipate the information needs of their
human team members, prepare and communicate task information,
adapt to changes in situation and changes to the capabilities
of other team members, and effectively support team member
mobility. We are working on constructing software agents
that can:
-
Integrate information retrieval with user-centered problem
solving and decision support;
-
Monitor and cache environmental information actively;
-
Form adaptive human and software agent teams as needed,
depending on task and information requirements;
-
Develop greater capacities for modeling users, situations,
and their own performance and capabilities;
-
Use their awareness of task and team interdependencies
to work together more effectively.
We
are drawing on cognitive science and human factors research
to understand how individuals and teams represent tasks.
Given that the goals of a team mission are often implicit,
it is crucial that team and individual tasks are represented
formally and explicitly. This will ensure that software
assistants are integrated smoothly into human teams. Thus,
key activities include identifying team and individual tasks,
allocating roles and functions for performing those tasks,
and defining task and role models for humans and their intelligent
assistants.
Co-training
is a key component of this research, which means that while
humans are adapting to the capabilities, rationales, and
behaviors of their software assistants, the software assistants
are learning to anticipate the informational needs of particular
human team members.
Finally,
our RETSINA agents enable successful
teamwork, as outlined in human factors research. The agents
we are developing support team situation assessment, enhance
team-supporting behaviors, enable more effective leadership,
make possible more efficient communication among team members,
and assist in conflict negotiation.
This
research has implications for other types of planning teams
that comprise multidisciplinary experts, including civilian
emergency response teams, management teams, and single service
military teams.
Related
Pages:
Messenger
Tie-3 Demo
Robotics
Institute Project Page