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    GTC Silicon Valley-2019 ID:S9315:Deep Learning for Robotics

    Pieter Abbeel(UC Berkeley | covariant.ai)
    Programming robots remains notoriously difficult. Equipping robots with the ability to learn would bypass the need for what often ends up being time-consuming task-specific programming. This talk will describe recent progress in deep reinforcement learning (robots learning through trial and error), in apprenticeship learning (robots learning from observing people), and in meta-learning for action (robots learning to learn). Our work has led to new robotic capabilities in manipulation, locomotion, and flight, with the same approach underlying advances in each of these domains.

    View the slides (pdf)