Social Reinforcement Learning

Natasha Jaques / Google Brain

Dec 21, 2020

Abstract: Social learning helps humans and animals rapidly adapt to new circumstances, and drives the emergence of complex learned behaviors. This talk focuses on Social Reinforcement Learning, developing new RL algorithms that leverage social learning to improve single-agent learning and generalization, multi-agent coordination, and human-AI interaction. We will demonstrate how a multi-agent technique for Adversarial Environment Generation based on minimax regret can lead to the generation of a complex curriculum of training environments, which improves an agent’s zero-shot transfer to unknown, single-agent test tasks. To improve multi-agent coordination, we give agents an intrinsic motivation to increase their causal influence over the actions of other agents, and show that this leads to the emergence of communication and enhances cooperation. Finally, we propose a novel Offline RL technique for learning from intrinsic social cues during interaction with humans in an open-domain dialog setting. Together, this work argues that Social RL is a valuable approach for developing more general, sophisticated, and human-compatible AI.

Bio: Natasha Jaques holds a joint position as a Research Scientist at Google Brain and post-doc at UC Berkeley. Her research focuses on social reinforcement learning---developing multi-agent RL algorithms that can improve single-agent learning, generalization, coordination, and human-AI collaboration. Natasha received her PhD from MIT, where she focused on Affective Computing and new techniques for deep/reinforcement/machine learning. Her work has received the best demo award at NeurIPS 2016, best paper at the NeurIPS ML for Healthcare workshop, and an honourable mention for best paper at ICML 2019. She has interned at DeepMind, Google Brain, and is an OpenAI Scholars mentor. Her work has been featured in Quartz, the MIT Technology Review, Boston Magazine, and on CBC radio. Natasha earned her Masters degree from the University of British Columbia, and undergraduate degrees in Computer Science and Psychology from the University of Regina