SocialRL Lab Photo
 

Welcome to the Social Reinforcement Learning lab website!

Social learning helps humans and animals learn complex behavior, rapidly adapt to new circumstances, and cooperate to achieve joint goals. Our lab is focused on whether Social Reinforcement Learning—algorithms that leverage social information in both human-AI and multi-agent interactions—can do the same thing for AI. Research areas include multi-agent reinforcement learning, learning from human feedback (RLHF), human-AI interaction and cooperation, social learning, modeling other agents’ goals and preferences, and emergent complexity.

Our lab was founded by Natasha Jaques in 2024 and is part of the Paul G. Allen School for Computer Science and Engineering at the University of Washington.

If you are a prospective Ph.D student or postdoc, please visit the contact page for more information on how to apply.

 

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