GT MAP Seminar: Prof. Evangelos Theodorou (GT AE)

This is a part of the GT MAP activities on Control.  GT MAP is a place for research discussion and collaboration. We welcome participation of any researcher interested in discussing his/her project and exchange ideas with Mathematicians.

There will be light refreshments through out the event. This seminar will be held in Skiles 006 and refreshments at Skiles Atrium.

A couple of members of Prof. Theodorou's group will present their research

3:00 PM - 3:45PM Prof. Theodorou will give a talk on " The science of autonomy: A "happy" symbiosis between learning, control and physics."

3:45PM -- 4:00PM Break with Discussions

4:00PM - 4:25PM another talk.

4:25PM - 5PM Discussion of open problems stemming from the presentations.


Title: The science of autonomy: A "happy" symbiosis between learning, control and physics.

 

Abstract:   In this talk I will present an information theoretic approach to stochastic optimal control and inference  that has advantages  over classical methodologies and theories for decision making under uncertainty.  The main idea  is that there are certain connections between optimality principles in control and information theoretic inequalities in statistical physics that allow  us to solve hard decision making problems in robotics, autonomous systems and beyond. There are essentially two different points of view  of the same "thing" and these two different points of view  overlap   for a fairly general class of dynamical systems that undergo stochastic effects.  I will also present a holistic view of autonomy that collapses planning, perception and control into one computational engine, and ask questions  such as  how organization and structure relates to computation and performance. The last part of my talk includes computational frameworks for uncertainty representation   and suggests ways to incorporate these representations within decision making and control.

 

 

Event Details

Date/Time:

  • Friday, March 9, 2018 - 3:00pm to 5:00pm

Fee(s):
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