"And so what happened was I programmed the robot. And it would run into the wall. And I would bring it back. And I would fix the programming. And it would run into the wall again, hopefully for a slightly different reason. And over the course of a couple of weeks, I managed to write a program that would use these funny sonar sensors on the robot and make it drive down the hall without crashing into the walls. And so that was good. And I was happy, in a way, at the end of that, that I had gotten it to work. But I reflected on that a bit more. And what I decided was that I had learned how to navigate down the hallway using the sonar sensors. And what I thought was that-- and it had taken a long time. And I was kind of a hassle. And really, the system should have been doing the learning, not me. So my view was that I should figure out a way to get out of the loop to build systems that could learn on their own to do stuff. And then I could just wait for them to do that. And that would be better. So that was flaky."
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Computer scientists from the United StatesWomen academics from the United StatesStanford University alumniWomen scientists from the United StatesMassachusetts Institute of Technology faculty
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Leslie P. Kaelbling
Leslie Pack Kaelbling is an American roboticist and the Panasonic Professor of Computer Science and Engineering at the Massachusetts Institute of Technology. She is widely recognized for adapting partially observable Markov decision processes from operations research for application in artificial intelligence and robotics. Kaelbling received the IJCAI Computers and Thought Award in 1997 for applying reinforcement learning to embedded control systems and developing programming tools for robot nav
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