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portfolio

research

Batch Exploration with Examples for Scalable Robotic Reinforcement Learning

Annie S. Chen, Hyunji Nam, Suraj Nair*, Chelsea Finn We propose a framework for leveraging weak human supervision to enable better robotic exploration for scalable data collection. Under this framework, the robot autonomously collects high quality data with a few minutes of human supervision, providing better data for downstream offline RL.

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DVD

Annie S. Chen, Suraj Nair, Chelsea Finn We propose a simple approach, Domain-agnostic Video Discriminator (DVD), that learns multitask reward functions by training a discriminator to classify whether two videos are performing the same task. These reward functions can generalize to unseen environments and tasks by learning from a small amount of robot data and a large, diverse dataset of in-the-wild human videos.

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talks

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

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Teaching experience 2

Workshop, University 1, Department, 2015

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