Combines different work pages with different tasks. Most parts was done with help This Youtube Channel, Thanks Author for the Great Resource!
(c) Well the environment spits out a state, the agent transforms that state using a differentiable function (typically a neural network) into a probability distribution over actions. It samples an action using that distribution, and executes it in the environment, which in turn spits out a new state and reward."
(c) Solving the flower problem. Our farmer wants to predict a flowers type, only knowing the width and length of its petal. We want to predict that last flowers color, and also end up with a neural network that can classify future flowers!
Based on source about Machine Larning on JS. And, what is important, projects don't represent Machine Larning, but simple example of generation and mutation flow.