The calculation is called simple because it follows directly from the definitions above. Simple means more like “follows directly from definition without fancy math tricks”, not " everyone who can read could solve this in 10 minutes".
I think this is also mostly math related, not physics?
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.
Its about a certain form of reinforced learning, called Temporal Difference Learning:
https://inria.hal.science/hal-00840470/document at page 11.
The calculation is called simple because it follows directly from the definitions above. Simple means more like “follows directly from definition without fancy math tricks”, not " everyone who can read could solve this in 10 minutes".
I think this is also mostly math related, not physics?
I had a good laugh anyway. Good meme
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.
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.