Leslie Pack Kaelbling is Professor of Computer Science and Engineering at the Computer Science and Artificial Intelligence Laboratory (CSAIL)at the Massachusetts Institute of Technology. She has made research contributions to decision-making under uncertainty, learning, and sensing with applications to robotics, with a particular focus on reinforcement learning and planning in partially observable domains.

She holds an A.B in Philosphy and a Ph.D. in Computer Science from Stanford University, and has had research positions at SRI International and Teleos Research and a faculty position at Brown University. She is the recipient of the US National Science Foundation Presidential Faculty Fellowship, the IJCAI Computers and Thought Award, and several teaching prizes and has been elected a fellow of the AAAI. She was the founder and editor-in-chief of the Journal of Machine Learning Research.

Intelligent Interaction with the Real World

Since the inception of the field if AI, one of the visions of artificial intelligence has been robust, intelligent, general-purpose robots that interact with the real world. We have made useful progress in that direction, but there is still a long way to go. I will characterize one view of how we might achieve this goal, describe some intermediate results, and characterize important technical and methodological problems that must be solved to make that vision real.

Videolecture