Natasha Jaques

Natasha Jaques talks about her PhD, her papers on Social Influence in Multi-Agent RL, ML & Climate Change, Sequential Social Dilemmas, internships at DeepMind and Google Brain, Autocurricula, and more!

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 Learning
Natasha Jaques, Angeliki Lazaridou, Edward Hughes, Caglar Gulcehre, Pedro A. Ortega, DJ Strouse, Joel Z. Leibo, Nando de Freitas

Tackling climate change with Machine Learning
David 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


Additional References

(c) 2019 Robin Ranjit Singh Chauhan