UTCS Colloquium/AI: Hod Lipson/Cornell University: Mining Experimental data for Dynamical Invariants - from Cognitive Robotics to Computational Biology TAY 3.128 Friday November 7 2008 11:00 a.m.

Contact Name: 
Jenna Whitney
Date: 
Nov 15, 2008 6:00pm

There is a signup schedule for this event (UT EID required).

Type of Talk: UTCS Colloquium/AI

Speaker/Affiliation: Hod Lipson/Corne ll University

Date/Time: Friday November 7 2008 11:00 a.m.
Host: Risto Miikkulainen

Talk Title:
Mining Experimental data for Dynamical Invariants - from Cognitive Robotics to Computational Biology

Talk Abstract:
This talk will describe new active learning proce sses for
automated modeling of dynamical systems across a number
of disciplines. One of the long-standing challenges in robotics
is achiev ing robust and adaptive performance under uncertainty.
The talk will de scribe an approach to adaptive behavior based
on self-modeling where a system continuously evolves multiple
simulators of itself in order to make useful predictions. The robot
is rewarded for actions that cause d isagreement among predictions
of different candidate simulators thereb y elucidating uncertainties.
The concept of self modeling will then be generalized to other systems
demonstrating how analytical invariants ca n be derived automatically
for physical systems purely from observation . Application to modeling
physical and biological systems will be shown .

Speaker Bio:
Hod Lipson is an Associate Professor of Mechanical & Aerospace
Engineering and Computing & Information Science at Cornell
University in Ithaca NY. He directs the Computational Synthesis
g roup which focuses on novel ways for automatic design fabrication
and adaptation of virtual and physical machines. He has led work in
areas such as evolutionary robotics multi-material functional rapid
prototyp ing machine self-replication and programmable self-assembly.
Lipson re ceived his Ph.D. from the Technion - Israel Institute of Tech-
nology in 1998 and continued to a postdoc at Brandeis University and
MIT. His r esearch focuses primarily on biologically-inspired approaches
as they bring new ideas to engineering and new engineering insights
into biology .