Graduate Student
Computer Science Division
523 Soda Hall
University of California
Berkeley, CA 94720-1776
(510) 642-2038
I am a Ph.D. candidate at U.C. Berkeley working in the area of machine learning. My research advisor is Stuart Russell. I attended Berkeley as an undergraduate receiving my BS in electrical engineering and computer sciences in 1998.
My current research interests include reinforcement learning and its application to motor control problems. Part of this research aims to reduce the variance in estimating policy gradients by reasoning about an agent’s sensor data. Improving the gradient estimation task allows us to build efficient learning algorithms. These algorithms are used to quickly learn effective controllers for a simulated dart throwing problem and for a simulated quadruped locomotion problem. You may watch some videos of agents performing these tasks.
I am also an active member of Black Graduate Engineering and Science Students (BGESS).
Here is a copy of my curriculum vitae.
Publications:
Gregory Lawrence and Stuart Russell. Improving Gradient Estimation by Incorporating Sensor Data. In Proceedings of the 24th International Conference on Uncertainty in Artifical Intelligence, Helsinki, Finland, 2008. [Abstract].Gregory Lawrence, Noah Cowan, and Stuart Russell. Efficient Gradient Estimation for Motor Control Learning. In Proceedings of the 19th International Conference on Uncertainty in Artificial Intelligence, Acapulco, Mexico, 2003. [Abstract].
Mark Paskin and Gregory Lawrence. Junction Tree Algorithms for Solving Sparse Linear Systems. Technical Report UCB/CSD-03-1271, University of California at Berkeley, 2003. [Abstract].