Python implementation of an AI Model that maps Lists of Inputs to Lists of Outputs with blended weights
I simply wanted to test a theory I had that I haven't seen explored yet where inputs and outputs are represented as integers where each bit is an on and off state of each node, with applied weight blending to help it generalize. It seems to work well from my test at the bottom (I intentionally amped up the Scoring Falloff and Mutation Rates for this test, so that I can test it further later on it's ability to generalize on unseen data.
If you expirement with this model, please share your results, I'd love to see it! :)