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Dana Kulic <[log in to unmask]>
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Dana Kulic <[log in to unmask]>
Tue, 26 May 2009 14:50:25 -0400
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RSS'09 Workshop on Bridging the gap between high-level discrete
representations and low-level continuous behaviors


The full-day workshop "Bridging the gap between high-level discrete
representations and low-level continuous behaviors" will be held during the
2009 Robotics: Science and Systems Conference in Seattle, Washington, USA,
on Sunday, June 28, 2009.   This workshop is supported by the Technical
Committee on Robot Learning of the IEEE Robotics and Automation Society.


Recently, robotics researchers have been investigating the modeling of human
and robot behavior in terms of motion primitives. This research direction,
based on biological and neuroscience findings, posits that human behavior is
composed of motor primitive units, which can be acquired by a robot through
imitation learning or practice. Motion primitives offer an approach for
discretizing continuous behavior, representing a "bottom-up" approach for
organizing robot behavior. On the other hand, in AI and planning fields,
there has been a longstanding area of research in planning and acting in the
discrete domain, or through modeling changes in the world as an
instantaneous change in discrete state. This approach can be thought of as a
"top-down" approach for organizing robot behavior. In this workshop, we
propose to bring together researchers from both areas to discuss approaches
for "bridging the gap" and combining continuous domain approaches with
discrete representations.

The aim of the workshop is to bring together researchers working on motion
primitives as a way of discretizing continuous behavior, and discuss ways in
which these approaches can be extended through hierarchical organization and
combined with planning and other discrete domain approaches. Specific themes
of the workshop include:

   - motion primitive representations and task abstractions
   - learning and parsing sequences and plans of motion primitives
   - imitation learning and learning from observation based on motion
   - hierarchical reinforcement learning
   - apprenticeship learning of composed tasks
   - hybrid task control
   - hierarchical organization of behaviors
   - learning operator conditions for primitives
   - plan recognition
   - plan generation and modification

The workshop will include talks by a number of the top researchers in the
field, who will articulate current approaches and the progress to date. A
key goal of the workshop is to provide a venue to allow discussion on how
current approaches may be combined to integrate the capability for acting in
the continuous domain while reasoning in the discrete domain.

Michael Beetz (TU Munich)
Chad Jenkins (Brown)
Danica Kragic (KTH)
Jun Morimoto  (ATR)
Aude Billard  (EPFL)
Michael Pardowitz (U. Bielefeld)
Tamin Asfour  (U. Karlsruhe)
Christopher Geib (Edinburgh)
Rod Grupen (U Mass)
Tetsunari Inamura (NII Japan)
Volker Krueger (Aalborg University)
Dieter Fox (U Washington)
Andrew Ng (Stanford)
Erion Plaku (Johns Hopkins)
Bhaskara Marthi (Willow Garage)
Hadas Kres-Grazit (Cornell)

For a detailed program and schedule, please refer to the workshop website:


Dana Kulic (U Waterloo)
Pieter Abbeel (Berkeley)
Jan Peters (Max Planck Institute)

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