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
gradient descent and stocastic gradient descent.