Machine Learning Math Experiments – a(n+1)/a(n) = 2 Where a = model( np.random.rand() )

Given c. A problem of finding a and b in c = a + b. Seems impossible when you only know c. From this I wonder if nature has solved problems like this by limiting probability.

Then coming up with a problem of your own. Like

a = model(np.random.rand())
a(n+1)/a(n) = 2 # some constant

Find a model() or function that solves this.

I did find a model() but it was perhaps to easy when it had some memory. One thing was odd. I had to use .5 as a 2 replacement and then 1/model(). From this I guess that a lot of machine learning are technical problems.

Which gives me an idea.

Why not use a try: except in the loop?