Distinguished Lecture Series - Leslie Pack Kaelbling/MIT Computer Science and Artificial Intelligence Laboratory, "Planning, estimation, and execution in complex robot domains", ACES 2.302

Contact Name: 
Jenna Whitney
Date: 
Oct 6, 2011 11:00am - 12:00pm

There is a sign-up schedule for this event that can be found at

http://apps.cs.utexas.edu/talkschedules/cgi/list_events.cgi

Type o

f Talk: Distinguished Lecture Series

Speaker/Affiliation: Leslie Pack

Kaelbling/MIT Computer Science and Artificial Intelligence Laboratory

Talk Audience: UTCS

Date/Time: Thursday, October 6, 2011, 11:00 a.m

.

Location: ACES 2.302

Host: Peter Stone

Talk Title: Plannin

g, estimation, and execution in complex robot domains

Talk Abstract:

The fields of AI and robotics have made great improvements in many indiv

idual subfields, including in motion planning, symbolic planning, probab

ilistic reasoning, perception, and learning. Our goal is to develop an i

ntegrated approach to solving very large problems that are hopelessly intra

ctable to solve optimally. We make a number of approximations during plann

ing, including serializing subtasks, factoring distributions, and determ

inizing stochastic dynamics, but regain robustness and effectiveness throu

gh a continuous state-estimation and replanning process. This work is in e

arly stages, but it has been demonstrated in simulation and on a real PR2

mobile manipulation problem.

Speaker Bio:
Leslie Pack Kaelbling is P

rofessor of Computer Science and Engineering and Research Director of the C

omputer Science and Artificial Intelligence Laboratory (CSAIL) at the Massa

chusetts Institute of Technology. She has previously held positions at Brow

n University, the Artificial Intelligence Center of SRI International, an

d at Teleos Research. She received an A. B. in Philosophy in 1983 and a Ph.
D. in Computer Science in 1990, both from Stanford University. Prof. Kael

bling has done substantial research on designing situated agents, mobile r

obotics, reinforcement learning, and decision-theoretic planning. In 2000

, she founded the Journal of Machine Learning Research, a high-quality jo

urnal that is both freely available electronically as well as published in

archival form; she currently serves as editor-in-chief. Prof. Kaelbling is
an NSF Presidential Faculty Fellow, a former member of the AAAI Executive
Council, the 1997 recipient of the IJCAI Computers and Thought Award, a

trustee of IJCAII and a fellow of the AAAI.