I've created a small simulation game and I have a basic neural network in place, each "creature" in my game has random weights on it's nodes and they all behave differently.
Their goal is to stay inside a circular "safe zone" that moves around the center of the game world. After 1000 generations of evolution not a single one of them makes any attempt to follow the circle around, so I was thinking I either..
Don't know how to train them properly
Don't know how to find who should live/ die.
Using the wrong input/ outputs.
Can anyone shed any light on what my issue is here? I'm sorry if this is vague I've only been using these for a couple of hours. But to elaborate on my question, what kind of inputs/ outputs should I be using with my neural network and what is the general procedure (in respect to my evolution approach) to train them to do the correct thing?? Could the error be caused by the number of nodes in the hidden layer or something?