当适应新的任务τiτi,模型参数由参数θθ变为θ′iθi′,在MAML,新任务的模型参数为θ′iθi′通过一次或更多的梯度下降更新θ′i=θ−a▽θLτi(fθ)θi′=θ−a▽θLτi(fθ) 4 Meta-Imitation Learning with MAML 在本节中,我们将描述如何将模型无关的元学习算法(MAML)扩展到模仿学习设置 ...
title: "[Draft] Imitation Learning" date: "2024-01-18" math: mathjax draft: true --- RL suffers from several drawbacks 1. Determining a reward function that represent the true performance objectives can be challenging. 2. The reward signal may be sparse > Imitation Learning : The reward ...
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