As a reminder today's OSU Robotics seminar will be presented by Reid Simmons from the Carnegie Mellon University, on "Agents that Learn and Teach".
The seminar will be from 10-11am, followed by an 11-11:30 student-only Q&A session.
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Seminar Title: Agents that Learn and Teach
Abstract:This talk will present recent work by my students who are investigating
how agents can learn from people and teach them effectively and
efficiently. In terms of learning, we have explored having agents use
multiple modes of interaction, such as providing demonstrations and
indicating preferences, to more effectively learn personal preferences.
On the teaching side, we have explored having agents use counterfactual
demonstrations, based on mental models of the learner, to efficiently
scaffold learning of the agent's policies. We have also explored how
providing non-verbal affective feedback can improve human learning, even
if the feedback does not provide any information relevant to the task at
hand. I'll also speculate on how this research can be used in assisting
the elderly and their caregivers, as part of the new NSF AI-CARING
Institute, of which CMU and OSU are both participants.
Bio: Reid Simmons is a Research Professor in Robotics and Computer Science at
Carnegie Mellon University. He is also the director of the
first-in-the-country undergraduate major in Artificial Intelligence.
Dr. Simmons earned his PhD from MIT in 1988 in the field of Artificial
Intelligence. Since coming to CMU in 1988, he has focused on developing
self-reliant robots that can autonomously operate over extended periods
of time in unknown, unstructured environments. Specific research
interests include human-robot social interaction, especially non-verbal
communication through affect, proxemics, motion, and gesture, task
planning under uncertainty, execution monitoring and failure recovery,
and coordination of multiple heterogeneous robots. He also served as a
Program Director at the National Science Foundation, where he oversaw
the National Robotics Initiative and Smart and Autonomous Systems programs.
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