"So one set of possible kind of general ideas includes convolution in space also and time. Maybe understanding the kinematics of the system that it's connected together in joints and segments, a notion of planning to move through space, being able to do causal reasoning-- if I were to do this, what would happen? -- Abstracting over individual objects, various kinds of state and temporal abstraction and so on. So our view-- I don't want to commit to a particular list-- but is that there's a list of structural principles that are pretty generic and very broadly useful and we should build them in."
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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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