Machine Learning for Autonomous Robot Actions

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I recently stumbled upon a scientific paper (here) related to building an autonomous robot controller with machine learning techniques. This article gave me the idea of using machine learning algorithms for controlling autonomous robot actions in FRC. This algorithm in particular seems somewhat applicable to what we do with our autonomous modes. Experiments with it also seem encouraging so far.

I was wondering if anything like this has been done before in FRC?

In addition, the algorithm outlined in the paper above employs a couple of sub-algorithms I am trying to implement. One is "iLQG"(paper about it here), and another is "Path Integral Policy Improvement". Has anyone had any experience with, or even heard of them before?