BriefGPT.xyz
Apr, 2019
机器人学习的高效监督:基于模仿、仿真和自适应的方法
Efficient Supervision for Robot Learning via Imitation, Simulation, and Adaptation
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Markus Wulfmeier
TL;DR
本研究旨在通过利用更强大的信息源和从现有数据中提取更多信息的方式,增加数据收集与维护流水线的效率,并着重解决模仿学习、领域自适应和从模拟中进行传输等三个正交方面的问题。
Abstract
Recent successes in
machine learning
have led to a shift in the design of
autonomous systems
, improving performance on existing tasks and rendering new applications possible. Data-focused approaches gain relevanc
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