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
Nov 7, 2008 11:00am - 12:00pm

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

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
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

roup which focuses on novel ways for automatic design fabrication
adaptation of virtual and physical machines. He has led work in

such as evolutionary robotics multi-material functional rapid

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