CFP: Supervisory Control and AI workshop

Call For Papers
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The AAAI-04 Workshop on
Supervisory Control of Learning and Adaptive Systems
To be held at the Nineteenth National Conference on
Artificial Intelligence (AAAI-04)
July 25 or July 26, 2004 in San Jose, CA
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With supervisory control, a human operator intermittently takes
control of a process that is otherwise controlled by a computer.
Supervisory control involves both autonomy and intelligence, although
the latter is normally attributed solely to the human operator. One
goal of this workshop, therefore, is to bring together researchers in
Robotics, Machine Learning, Human-Computer Interaction and other areas
to explore the role of supervisory control for AI systems, especially
for systems where both human and machine share the ability to learn
and adapt to changing circumstances.
In the past, supervisory control has focused primarily on traditional
applications of telerobotics, such as hazardous waste disposal,
planetary and undersea exploration, and remote surveillance and
repair. These applications remain important areas of research today,
although in recent years supervisory control has become much more
pervasive than we often realize. Assistive technology for the
physically handicapped, software agents for electronic commerce, and
education technology for the modern classroom are all examples where
shared control by human and machine will have increasing societal
impact. Thus, another goal of this workshop is to identify real-world
applications where the combination of supervisory control and AI will
have the most impact. Specific questions for discussion include the
following:
* How should the user interface convey to the human operator the
capabilities and learning progress of the AI system?
*
What information is required for the human operator to develop a
trust in the AI system?
* Is there a principled way for an AI system to infer the intentions
of, and take control from its human supervisor?
*
What heuristics or user models can be used to speed up what is
essentially a transfer of knowledge from human to machine?
* Which learning algorithms are suitable for short time scales where
data are abundant and for long time scales where data are relatively
sparse?
*
How should the learning system go about improving its capabilities
beyond those of the human supervisor?
* Under what conditions can another AI system act as supervisor and
for what conditions should a human always remain in the loop?
TOPICS
Areas of interest for this workshop include, but are not limited to
the following:
*
Adjustable autonomy/Mixed initiative control
* Co-learning
*
Assistive technology
* Adaptive user interfaces
*
Telerobotics
* Human-robot interaction
*
Acquisition of transparent user models
* Fault-tolerant learning
*
Learning from demonstration
* Evaluation methods
FORMAT
This one-day workshop will consist of a keynote talk of general
interest, followed by several invited talks and paper presentations on
more focused topics. Panels will be used when appropriate to
facilitate discussion of clusters of closely related talks.
Depending on the submissions, the workshop may include a poster
session to encourage more in-depth discussions.
SUBMISSIONS
Participants are required to submit either a technical paper (roughly
six pages in the conference format) or else an abstract (up to two
pages) describing research relevant to the workshop. Submissions
should be sent via email to one of the co-chairs and should be in
Postscript, PDF, or MS Word format. If the papers are of sufficient
quantity and quality, we will seek to publish them as an edited book
or journal special issue.
CHAIRS
Mike Rosenstein Mohammad Ghavamzadeh
Department of Computer Science Department of Computer Science
Univ. of Massachusetts Amherst Univ. of Massachusetts Amherst
140 Governors Drive 140 Governors Drive
Amherst, MA 01003 Amherst, MA 01003
Voice: 413-545-1876 Voice: 413-545-1596
Fax: 413-545-1249 Fax: 413-545-1249
Email: snipped-for-privacy@cs.umass.edu Email: snipped-for-privacy@cs.umass.edu
WWW:
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WWW:
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COMMITTEE
Chuck Anderson, Colorado State University ( snipped-for-privacy@cs.colostate.edu)
Mathias Bauer, German Research Center for AI ( snipped-for-privacy@dfki.de)
Rob St. Amant, North Carolina State University ( snipped-for-privacy@csc.ncsu.edu)
Holly Yanco, University of Massachusetts Lowell ( snipped-for-privacy@cs.uml.edu)
IMPORTANT DATES
* Technical submissions and abstracts due: March 12, 2004
*
Notification of acceptance: April 16, 2004
* Camera ready copies due: May 25, 2004
*
Workshop date: TBD, either July 25 or July 26, 2004
WEBSITE:
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