Imagine neural networks.
okay well let's imagine we separate three neural networks
one decides what's the important input
one decides what that input should really be (replace 1 with 3's)
last makes the final decision
This is just a concept, I have no reason even imaginary reason to think why it would work, but it sounds fun.
It has been a long time since i've posted, i have have a few ideas like this and others
How about neural networks that first train by "learning the rules". One neural network that observes winning situations during training could vote on whether or not the move is a winning move, one can vote on whether or not the move is a losing move. And the third one can either 1. not be a neural network and just decide based on which move has the highest ranking. or 2. be a neural network that takes those decisions and that of the entirety of the board to make a final decision.
My idea right now that I'm actually working on is highly different from the two ideas mentioned above.
An individual 'neuron' in a neural network does three things.
1. gets input
2.adds all that input
3. compares the sum to a number aka "threshold"
4. sends out a number (aka "weight" )based on if the threshold was reached. this number is sent to another neuron or used to determine the final output.
well I ask, why not bend the rules?who said these rules were necessarily the best rules. I know one can optimize neural networks that function this way to find some local minimum of error. but perhaps some other organization is more flexible, and can find a better minimum faster and more consistently. more later