If something is complex enough assume a network. Here I speculate about the position of an object. In machine learning terms this position ?would be a classification.
That is. You have a set of integer numbers as the grid points. Then you get a position grid by hot encoding it like [1,0,0,0,0,0,0,0,0,0]. Here the object start a index zero. Then when you calculate a new position with pos_x = model(…) you could get something like [0.1,0.8,0.1,0,0,0,0,0,0]. I assume this can reflect the probability of the next position. Also I assume the misclassification are important.
If the universe is taking advantage of networks. Then this would be a general misclassification problem. But then again. Why not take advantage of the 0.1 misclassification. I wonder if this could be a way to get continuous movement. That is. You have a large but limited number of grid points and just probability in-between.
So the probability is tied to the grid points. Then at each iteration the probability of the position of the object changes. Then a goal of the universe is to control the speed of probability. The speed of the object.