"So OK, I finished my PhD. And I thought, OK, I know something about robot learning now. But I really want to make robots that can do complicated things. And I couldn't figure out how to get basic reinforcement learning methods to really scale up to problems that I cared about. And so this is one last flight. I'll show you from some talk that I gave in 1995. And I kind of complained that the ideal that you could take just a big bunch of what I like to call neural goo now, just a big bunch of generic neural network stuff, and train it to be an intelligent agent all by itself. But that wasn't going to be feasible. And instead, we needed some kind of compositional structure. And that would give us more efficient learning and more robust behavior and so on."
Quote Details
Added by wikiquote-import-bot
Unverified quote
0 likes
Computer scientists from the United StatesWomen academics from the United StatesStanford University alumniWomen scientists from the United StatesMassachusetts Institute of Technology faculty
Original Language: English
Available Languages (1)
Sources
Imported from EN Wikiquote
https://en.wikiquote.org/wiki/Leslie_P._Kaelbling
Revision History
No revisions have been submitted for this quote.
Categories
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
33 quotes on TrueQuotesView all quotes by Leslie P. Kaelbling →
Related Quotes
"Fundamentally, the way we think about it is that we decompose the computation that's in the robot's head now into two…"
"So the dimensionality of the space is kind of unthinkably high. It's also not exactly clear what constitutes an objec…"
"And so any approach that works effectively in a domain like this is going to have to handle very large spaces, very l…"
"The reason I want to start by backing all the way up to this like very basic control theory picture is that right now…"
"So one way to think about the whole problem set up then is that I, as the robotics engineer, have to do for my robots…"
"So I imagine that there's some distribution over possible environments that the robot could find itself in when it ac…"
"And so what we want to do is think about first of all, what's the best-- what would be the best pi to put inside the …"
"But the problem is now I've written down an objective function. I've said, "Oh, if you could tell me a distribution o…"
"So there are a bunch of ways you can think about the problem. I mean, one would be to say, "Oh, I'm really lazy. I do…"
"So imagine that you have some kind of probability distribution over the worlds that the robot could actually end up o…"