Abstract: In this talk I will cover some of the recent work out of the Socially Intelligent Machines Lab at UT Austin (http://sim.ece.utexas.edu/research.html). The vision of our research is to enable robots to function in dynamic human environments by allowing them to flexibly adapt their skill set via learning interactions with end-users. We explore the ways in which Machine Learning agents can exploit principles of human social learning, and breakdown assumptions about what “data” will be like, when the source of that data is an average human teacher. I will cover our work on interactive reinforcement learning algorithms that model the attention of the teacher; coupling learning from demonstration with simulation to make the best use of valuable interactions with people; and algorithms for re-using previously learned tasks in new contexts with the help of a teacher’s hints and corrections.  In the latter part of the talk, I will put on my other hat, as co-founder and CEO of Diligent Robotics (http://diligentrobots.com/about) to tell you about how we are translating our research on adapting to human environments into a commercial product. Our first product, Moxi, is a robot assistant that works alongside and supports clinical care teams in hospitals. Moxi was launched into beta trials late last year, and has been deployed in four hospitals across Texas to date.

Brief Bio: Andrea Thomaz is an Associate Professor and holds the William J. Murray, Jr. Fellowship in Engineering #3 in the Deaprtment of Electrical and Computer Engineering at The University of Texas at Austin. Prof. Thomaz joined Texas ECE in January 2016 after serving as an Associate Professor of Interactive Computing at the Georgia Institute of Technology from 2007-2016. She earned a B.S. in Electrical and Computer Engineering from the University of Texas at Austin in 1999, and Sc.M. and Ph.D. degrees from MIT in 2002 and 2006. Andrea is published in the areas of Artificial Intelligence, Robotics, and Human-Robot Interaction. Her research aims to computationally model mechanisms of human social learning in order to build social robots and other machines that are intuitive for everyday people to teach. Prof. Thomaz received an NSF CAREER award in 2010 and an Office of Naval Research Young Investigator Award in 2008. She was named to Popular Science magazine’s Brilliant 10 List(link is external) in 2012. In 2009, she was named to the MIT Tech Review Top Young Innovators Under 35.

Host: Henny Admoni

For Appointments: Keyla Cook (keylac@cs.cmu.edu)