this project uses a genetic algorithm to find the all 17 weights of this neural network to map 2 inputs to one output. green circles are biases and always have a weight of 1
How the genetic algorithm works (step by step): 1. create 10 sets of 17 random weights 2. run them all through the neural network and select the 2 best sets that have the lowest error (highest fitness) 3.delete all of the old sets and create 10 new sets based on the 2 best sets in step 2. 4. all of the 10 new sets have a 1/10 chance of mutating (having 4 of 17 values set to random again) How the neural network works: watch this video: https://youtu.be/bxe2T-V8XRs?t=2m31s
