[Ml-stat-talks] Fwd: [talks] Colloquium Speaker: Igor Mordatch, Wednesday, March 23, 4:30pm

Barbara Engelhardt bee at princeton.edu
Tue Mar 22 10:50:44 EDT 2016

Talk of interest.

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Colloquium Speaker
Igor Mordatch, University of California, Berkeley
Wednesday, March 23, 4:30pm
Computer Science 105

Automated Discovery and Learning of Complex Movement Behaviours

In order to create truly autonomous physical robots, understand the
underlying principles behind human movement, or tell narratives in animated
films and interactive games, it is necessary to synthesize movement
behaviours with the same wide variety, richness and complexity observed in
humans and other animals. Moreover, these behaviours should be discovered
automatically from only a few core principles, and not be a result of
extensive manual engineering or a mimicking of demonstrations. In this talk
at the intersection of robotics, computer graphics and biomechanics, I will
show work on novel trajectory and policy optimization methods that give
rise to a range of behaviours such getting up, climbing, moving objects,
hand manipulation, acrobatics, and various cooperative actions involving
multiple characters all in a single system. The resulting movements can be
used to successfully control a physical bipedal robot and coupled with
detailed models of human physiology, motions that match real human motion
can be produced de novo, giving the predictive power to conduct virtual
biomechanics experiments. The approach is fully automatic, based on general
neural network policy representations and does not require domain knowledge
specific to each behaviour, pre-existing examples or motion capture data.
Although discovery and learning are computationally-expensive and rely on
cloud and GPU computing, the interactive animation can run in real-time on
any hardware once the controllers are learned.

Igor Mordatch is a post-doctoral fellow working with professor Pieter
Abbeel at University of California, Berkeley. He received his PhD at
University of Washington under supervision of Emanuel Todorov and Zoran
Popovic and undergraduate degree in Computer Science and Mathematics at
University of Toronto. He worked as a visiting researcher at Stanford
University and Pixar Research. His research interests lie in the
development and use of optimal control and machine learning techniques for
robotics, computer graphics, and biomechanics.

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Barbara E Engelhardt
Assistant Professor
Department of Computer Science
Center for Statistics and Machine Learning
Princeton University
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