Lockheed Martin Robotics Seminar: Leslie Kaelbling, "Making Robots Behave"
Friday, May 4, 2018
2216 JM Patterson
301 405 4358
Lockheed Martin Robotics Seminar
Making Robots Behave
Computer Science & Artificial Intelligence Lab
Massachusetts Institute of Technology
The fields of AI and robotics have made great improvements in many individual subfields, including in motion planning, symbolic planning, probabilistic reasoning, perception, and learning. Our goal is to develop an integrated approach to solving very large problems that are hopelessly intractable to solve optimally. We make a number of approximations during planning, including serializing subtasks, factoring distributions, and determinizing stochastic dynamics, but regain robustness and effectiveness through a continuous state-estimation and replanning process. I will describe our initial approach to this problem, as well as recent work on improving effectiveness and efficiency through multiple types of learning.
Leslie Kaelbling is a Professor at MIT. She has an undergraduate degree in Philosophy and a PhD in Computer Science from Stanford, and was previously on the faculty at Brown University. She was the founding editor-in-chief of the Journal of Machine Learning Research. Her research agenda is to make intelligent robots using methods including probabilistic reasoning, planning, and reinforcement learning. She is not a robot.