Interview with Prof. Ramamoorthy about free agents and transfer learning in control of SRCMR in the tenth episode of the Flexible Elements podcast.

Prof.  Subramanian Ramamoorthy

Prof. Subramanian Ramamoorthy

In this episode I talk to Prof. Subramanian Ramamoorthy.
He tells us how he got started in robotics and how he first saw
the strengths of the modular concept. He saw this in National
Instruments’ use of modularity for building electronic testing
instruments that fit a specific situation rather than being large
“do it all” monoliths.

We talk about his use of free agents in control of SRCMR,
and how they can be used to interact with a dynamic world
by constantly adapting to it. Prof. Ramamoorthy also introduces
the concept of transfer learning. He explains how he and
Dr Hassan-Mahmud are currently exploring how we can reuse
learning by transferring what we learnt in one situation to another,
slightly different situation. This is especially interesting for SRCMR,
as they can adapt much more to the situation than a regular robot.



Dr. Subramanian Ramamoorthyis a Lecturer in Robotics at the School of
Informatics, University of Edinburgh, since 2007. Previously, he received a
PhD in Electrical and Computer Engineering from The University of Texas at
Austin. His current research work is focused on problems of autonomous decision
making over time and under uncertainty, by long-lived agents and agent teams
interacting with continually changing worlds. These problems are solved
using a combination of methods including layered representations involving
geometric/topological abstractions, game theoretic and related models of
inter-dependent decision making, and machine learning with emphasis on
issues of transfer and continual learning, reinforcement learning, etc.
He has twice been a finalist for the Best Paper Award at major international
conferences in the field of robotics – ICRA 2008 and IROS 2010, He
leads Team Edinferno, the first UK entry in the Standard Platform League at
the RoboCup International Competition.


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