"Many recent works focus on using expensive reinforcement learning (RL)
methods to solve this problem (Sermanet et al., 2018; Liu et al., 2017; Peng et 
al., 2018; Aytar et al.,
2018). In contrast, high-fidelity imitation in humans is often cheap: in 
one-shot we can closely mimic
a demonstration. Inspired by this, we introduce a meta-learning approach 
(MetaMimic — Figure 1)
to learn high-fidelity one-shot imitation policies by off-policy RL. These 
policies, when deployed,
require a single demonstration as input in order to mimic the new skill being 
demonstrated."
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Artificial General Intelligence List: AGI
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