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Mechanical and Civil Engineering Seminar

Thursday, April 4, 2019
11:00am to 12:00pm
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Gates-Thomas 135
Learning in Human-Robot Interaction: Optimization as an Inductive Bias
Anca Dragan, Assistant Professor, Department of Electrical Engineering and Computer Sciences, University of California, Berkeley,

Generating robot action for interaction with people is not scalable without learning, but learning from scratch has too high sample complexity. Inductive bias becomes critical, but what is the right inductive bias when it comes to people? We study the assumption that people are driven by intentions and are approximately rational in pursuing them. We derive algorithms that can leverage this assumption, as well as ways in which robots can remain flexible to human behavior that violates it.

For more information, please contact Carolina Oseguera by phone at 626-395-4271 or by email at [email protected].