Reid Simmons, Research Professor
Robotics and Computer Science
Carnegie Mellon University

Abstract
his 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.