Co-Sponsor(s)
Duke Computer Science; Duke Mechanical and Engineering and Materials Science
Lunch will be served at 11:45 AM.
While there have been huge advances in Machine Learning in recent years, many of the successes have relied on immense amounts of training data. Especially for sequential-decision-making tasks (the realm of reinforcement learning), obtaining such data from online experience can take a very long time. On the other hand, learning can often be dramatically accelerated by leveraging human input, for example as demonstrations of successful task executions, as interventions to correct mistakes, or simply as evaluative feedback separating "correct" actions from incorrect actions. This talk focuses on such Human-in-the-Loop Machine Learning for robotics tasks, covering both navigation, especially in tightly constrained spaces and manipulation in open-world settings.
Dr. Peter Stone holds the Truchard Foundation Chair in Computer Science at the University of Texas at Austin. He is Associate Chair of the Computer Science Department, as well as Director of Texas Robotics. In 2013 he was awarded the University of Texas System Regents' Outstanding Teaching Award and in 2014 he was inducted into the UT Austin Academy of Distinguished Teachers, earning him the title of University Distinguished Teaching Professor. Professor Stone's research interests in Artificial Intelligence include machine learning (especially reinforcement learning), multiagent systems, and robotics. Professor Stone received his Ph.D in Computer Science in 1998 from Carnegie Mellon University. From 1999 to 2002 he was a Senior Technical Staff Member in the Artificial Intelligence Principles Research Department at AT&T Labs - Research. He is an Alfred P. Sloan Research Fellow, Guggenheim Fellow, AAAI Fellow, IEEE Fellow, AAAS Fellow, ACM Fellow, Fulbright Scholar, and 2004 ONR Young Investigator. In 2007 he received the prestigious IJCAI Computers and Thought Award, given biannually to the top AI researcher under the age of 35, and in 2016 he was awarded the ACM/SIGAI Autonomous Agents Research Award. Professor Stone co-founded Cogitai, Inc., a startup company focused on continual learning, in 2015, and currently serves as Chief Scientist of Sony AI.
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Duke Computer Science; Duke Mechanical and Engineering and Materials Science