Reinforcement learning is a machine learning (ML) technique (“AI” in layman terms) for optimizing neural networks and other types of non-linear models.
As far as ML math goes, this is fairly tame. It looks complicated, but is spelled out clearly in the paper. A lot of these kind of theoretical papers — things that would get published in Automatica — are going to lean very heavy on math.
Source: PhD in Computer Science with dissertation using neural networks.
Septian@lemmy.zip 5 months ago
We’ve got the time dependent polar Schrödinger equation any time we want to pull out a ridiculous looking equation in pre-graduate level physics.