The following is a conversation with Leslie Kalebling. She is a roboticist and professor at MIT.

She is recognized for her work and reinforcement learning, planning, robot navigation,

and several other topics in AI. She won the Idge Kai Computers and Thought Award and was the

Editor-in-Chief of the prestigious journal Machine Learning Research. This conversation is part

of the Artificial Intelligence Podcast at MIT and beyond. If you enjoy it, subscribe on YouTube,

iTunes, or simply connect with me on Twitter at Lex Friedman spelled F-R-I-D. And now,

here's my conversation with Leslie Kalebling.

What made me get excited about AI? I can say that is I read Gertel Escherbach when I was in high

school. That was pretty formative for me because it exposed the interestiness of

primitives and combination and how you can make complex things out of simple parts.

And ideas of AI and what kinds of programs might generate intelligent behavior.

So you first fell in love with AI reasoning logic versus robots?

Yeah, the robots came because my first job, so I finished the undergraduate degree in philosophy at

Stanford, and was about to finish Masters in Computer Science, and I got hired at SRI

in their AI lab. And they were building a robot. It was a kind of a follow-on to shaky,

but all the shaky people were not there anymore. And so my job was to try to get this robot to do

stuff, and that's really kind of what got me interested in robots.

So maybe taking a small step back, your bachelor's in Stanford and philosophy did the Masters in

Computer Science, but the bachelor's in Philosophy. So what was that journey like? What elements of

philosophy do you think you bring to your work in computer science?

So it's surprisingly relevant. So the part of the reason that I didn't do a computer science

undergraduate degree was that there wasn't one at Stanford at the time, but that there's a part of

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