Tuesday, March 1, 2016 - 12:00pm
Location:3305 Newell-Simon Hall
Speaker:LESLIE PACK KAELBLING, Panasonic Professor of Computer Science and Engineering http://people.csail.mit.edu/lpk/
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 correctness and efficiency through learning.