[robotics-worldwide] Final CFP -- AAAI Agents the Learn from Human Teachers

Andrea Thomaz athomaz at cc.gatech.edu
Tue Sep 23 14:50:15 PDT 2008

Call for Papers:

AAAI Spring Symposium
Agents that Learn from Human Teachers

March 23-25, Stanford University
Submissions due: Oct 3

This AAAI Spring Symposium aims to bring together a multi-disciplinary
group of researchers to discuss how we can enable agents to learn from
real-time interaction with an everyday human partner, exploring the
ways in which machine learning can take advantage of elements of
human-like social learning.

The goal of this meeting is to foster a collaborative dialog and bring
multiple perspectives to bear on this challenge.  We are seeking broad
participation from researchers in:

  1. Machine Learning
  2. Human-Computer Interaction
  3. Human-Robot Interaction
  4. Intelligent User Interfaces
  5. Developmental Psychology
  6. Artificial Intelligence
  7. Adaptive systems
  8. Cognitive Science
  9. Computer Games
  10.Other related fields

We believe that learning will be a key component to the successful
application of intelligent agents in everyday human environments
(physical and virtual).  It will be impossible to give agents all of
the knowledge and skills a priori that they will need to serve useful
long term roles in our dynamic world. The ability for everyday users,
not experts, to adapt their behavior easily will be key to their
success. Machine Learning (ML) techniques have had much success over
the years when applied to agents, but ML techniques have not yet been
specifically designed for learning from non-expert users and current
techniques are generally not suited for it out of the box.

The symposium's program will cover a variety of topics at the
intersection of the various disciplines listed above.  For example:

  1. How do everyday people approach the task of teaching autonomous  
  2. What mechanisms of human social learning will machine learning  
agents need?
  3. Are there machine learning algorithms that are more/less amenable  
to learning with non-expert human teachers?
  4. What are proper evaluation metrics for social machine learning  
  5. What is the state of the art in human teachable systems?
  6. What are the grand challenges in building agents that learn from  

We welcome short and long papers, position statements, videos, and
demo proposals as well as panel proposals (indicating the names,
affiliations, and email addresses for all panelists).  Please submit
your paper of 2-8 pages in PDF AAAI submission format
to the Learning From Humans submission site:

Submissions will be judged on technical merit and on potential to
generate discussion and create community collaboration. Submissions
describing ongoing or completed work are strongly encouraged to
include a video or a live-demo proposal as well.

The organizers will prepare a technical report summarizing the
workshop.  Please direct any submission inquires to
aaaiss09lfh at easychair.org.
Andrea Thomaz
Asst. Professor, Interactive Computing
Georgia Institute of Technology

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