[robotics-worldwide] CFP: AAMAS 2010 Workshop on Agents Learning Interactively from Human Teachers

Sonia Chernova chernova at mit.edu
Mon Jan 11 05:54:15 PST 2010


  Call for Papers

  Agents Learning Interactively from Human Teachers

  Workshop @ AAMAS 2010
  Toronto, Canada, May 10th or 11th, 2010
  (exact date will be announced soon)



Learning is a key component to the successful application of
intelligent physical and virtual agents in everyday human
environments.  Research in interactive learning focuses on enabling
agents to learn from teachers the way that people do.

Interactive learning encompasses a wide range of approaches and is
referenced under many names, including teachable agents, imitation,
learning from demonstration, active learning, interactive shaping, and
bootstrapped learning.  This workshop aims to advance research in
interactive learning by bringing together researchers with different
approaches and attempting to establish standards for comparing
systems, evaluating their performance, and combining results from
different aspects of the problem.

The potential application domains for interactive learning are many --
both for embodied and for virtual agents -- and range across a spectrum
of abstractness from fine motor skills to deep abstract knowledge such
as that acquired at a university.  An interactive learning system
therefore may be formulated in a variety of ways, and we encourage a
broad spectrum of applications.  In particular, we welcome
contributions from both the software and robotic agents communities.
One of our main goals is to bridge this divide, to create a single
community of research on interactive learning agents.  To aid in
communication across this interdisciplinary collection of researchers,
authors are asked that in descriptions of their work they address the
following questions:

- How explicitly pedagogical is the human teacher?  At one extreme,
the human is a role-model not considering the agent at all; at the
other, the human is carefully formulating a curriculum.
- How dependent is learning on communication between human teacher and
agent?  At one extreme, the human and agent merely observe one another
interacting with the environment; at the other there is a complex
dialogue between teacher and student.
- How interdependent is learned information?  At one extreme, learning
can potentially happen in any order (e.g., mapping a state space); at
the other, each new piece of knowledge must be formulated in terms of
the previous one (e.g., Kirchoff's laws depend on current and voltage).
- What is the relative importance of how learning occurs vs. the end
result of learning in the research?  At one extreme, learning from
humans is just a pragmatic way of configuring a real-world system; at
the other, the system is only valued for the insight it provides on
human learning.

Target Audience
The goal of this workshop is to increase awareness and interest in
interactive learning methods, and to foster collaboration between
researchers across many disciplines.  We are seeking broad
participation from researchers in the areas of:

- Artificial Intelligence
- Learning from Demonstration
- Teachable Agents
- Education
- Human-Computer Interaction
- Human-Robot Interaction
- Intelligent User Interfaces
- Developmental Psychology
- Adaptive systems
- Cognitive Science
- Computer Games
- Other related fields

Important Dates and Deadlines
Deadline for the submission of papers:  FEBRUARY,  2, 2010
Notification of acceptance/rejection:  MARCH 2, 2010
Deadline for the receipt of camera-ready papers:  MARCH 19, 2010
Workshop: MAY 10th or 11th, 2010

Submission Instructions
We invite short and long length papers, reviews, and position papers.
Submissions will be judged on technical merit, the potential to
generate discussion, and their ability to foster collaboration within
the community.  Additionally, authors are asked to address the
bulleted questions above as appropriate.   The maximum length is 6
pages.  The style for papers in the proceedings follows the style of
the main conference which can be found on

Organizing Committee
Jacob Beal (Raytheon BBN Technologies)
Sonia Chernova (MIT Media Lab)
Brenna Argall (Ecole Polytechnique Fédérale de Lausanne)
W. Bradley Knox (University of Texas at Austin)
Daniel Oblinger (DARPA IPTO)
Matthew E. Taylor (The University of Southern California)
Andrea Thomaz (Georgia Tech)

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