Intuition for research in Social Reinforcement Learning | Natasha Jacques

Watch the full conversation here: How can we build intuition for interdisciplinary fields in order to tackle challenges in social reinforcement learning. Natasha Jaques is currently a Research Scientist at Google Brain and post-doc fellow at UC Berkeley , where her research interests are in designing multi-agent RL algorithms while focusing on social reinforcement learning. She received her PhD from MIT and has also received multiple awards for her research works submitted to venues like ICML and NeurIPS She has interned at DeepMind , Google Brain, and is an OpenAI Scholars mentor. Also check-out these talks on all available podcast platforms: About the Host: Jay is a PhD student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis. Jay Shah: You can reach out to ~jgshah1/ for any queries. Stay tu