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TalkRL: The Reinforcement Learning Podcast - Natasha Jaques

Natasha Jaques

08/09/19 • 50 min

1 Listener

TalkRL: The Reinforcement Learning Podcast

Natasha Jaques is a PhD candidate at MIT working on affective and social intelligence. She has interned with DeepMind and Google Brain, and was an OpenAI Scholars mentor. Her paper “Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning” received an honourable mention for best paper at ICML 2019.

Featured References

Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement LearningNatasha Jaques, Angeliki Lazaridou, Edward Hughes, Caglar Gulcehre, Pedro A. Ortega, DJ Strouse, Joel Z. Leibo, Nando de Freitas

Tackling climate change with Machine LearningDavid Rolnick, Priya L. Donti, Lynn H. Kaack, Kelly Kochanski, Alexandre Lacoste, Kris Sankaran, Andrew Slavin Ross, Nikola Milojevic-Dupont, Natasha Jaques, Anna Waldman-Brown, Alexandra Luccioni, Tegan Maharaj, Evan D. Sherwin, S. Karthik Mukkavilli, Konrad P. Kording, Carla Gomes, Andrew Y. Ng, Demis Hassabis, John C. Platt, Felix Creutzig, Jennifer Chayes, Yoshua Bengio

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Natasha Jaques is a PhD candidate at MIT working on affective and social intelligence. She has interned with DeepMind and Google Brain, and was an OpenAI Scholars mentor. Her paper “Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning” received an honourable mention for best paper at ICML 2019.

Featured References

Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement LearningNatasha Jaques, Angeliki Lazaridou, Edward Hughes, Caglar Gulcehre, Pedro A. Ortega, DJ Strouse, Joel Z. Leibo, Nando de Freitas

Tackling climate change with Machine LearningDavid Rolnick, Priya L. Donti, Lynn H. Kaack, Kelly Kochanski, Alexandre Lacoste, Kris Sankaran, Andrew Slavin Ross, Nikola Milojevic-Dupont, Natasha Jaques, Anna Waldman-Brown, Alexandra Luccioni, Tegan Maharaj, Evan D. Sherwin, S. Karthik Mukkavilli, Konrad P. Kording, Carla Gomes, Andrew Y. Ng, Demis Hassabis, John C. Platt, Felix Creutzig, Jennifer Chayes, Yoshua Bengio

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Previous Episode

undefined - About TalkRL Podcast: All Reinforcement Learning, All the Time

About TalkRL Podcast: All Reinforcement Learning, All the Time

August 2, 2019

Transcript

The idea with TalkRL Podcast is to hear from brilliant folks from across the world of Reinforcement Learning, both research and applications. As much as possible, I want to hear from them in their own language. I try to get to know as much as I can about their work before hand.

And Im not here to convert anyone, I want to reach people who are already into RL. So we wont stop to explain what a value function is, for example. Though we also wont assume everyone has read the very latest papers.

Why am I doing this? Because it’s a great way to learn from the most inspiring people in the field! There’s so much happening in the universe of RL, and there’s tons of interesting angles and so many fascinating minds to learn from.

Now I know there is no shortage of books, papers, and lectures, but so much goes unsaid.

I mean I guess if you work at MILA or AMII or Vector Institute, you might be having these conversations over coffee all the time, but I live in a little village in the woods in BC, so for me, these remote interviews are like a great way to have these conversations, and I hope sharing with the community makes it more worthwhile for everyone.

In terms of format, the first 2 episodes were interviews in longer form, around an hour long. Going forward, some may be a lot shorter, it depends on the guest.

If you want want to be a guest or suggest a guest, goto talkrl.com/about, you will find a link to a suggestion form.

Thanks for listening!

Next Episode

undefined - Michael Littman

Michael Littman

Michael L Littman is a professor of Computer Science at Brown University. He was elected ACM Fellow in 2018 "For contributions to the design and analysis of sequential decision making algorithms in artificial intelligence".

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