Some tips regarding the optimization problem based on the ML apprach


The general idea to find the good combination

Different between the RL and the genetic algorithm. This is a really good explanation, the core thing is that if there are interaction in a time sequenced way for teh RL approach.

Some examples about the flow fluid and the RL things

This one has a good figure to show different categories of the ML approach and their typical use case scenarios.
Machine Learning for Fluid Mechanics
Steven L. Brunton,1 Bernd R. Noack,2,3 and Petros Koumoutsakos4

Linear and non-linear optimization

Figure out optimization problem, control problem and optimization control problem

difference between deep learning, optimization control, reinforcement learning, it is a good blog. it first distinguish between the dl vs optimal control and RL, and then it distinguish betweem the RL and optimization control

Try to distinguish it is linear or non-linear optimization problem

reinforcement learning is used for non-linear control problem

Least square optimization


gradient descent and stocastic gradient descent.