Q Learning Neural network for tic tac toe Input implementation problem

Question

I've recently become interested in machine learning, specifically neural networks, and after creating ones to solve basic problems such as XOR and Sin and Cos graphs, however i am now looking into reinforcement learning and specifically q learning with neural networks, to try this out and see if i could implement this, i used a q learning neural network for tic tac toe. However I am unsure as to why my program does not learn correctly. One idea I have is that i have implemented the input neurons incorrectly.I am using visual basic console application so just let me know if you need me to post any code

My view on how to implement this:

Use 18 input neurons and have the first 9 being the state before placing a move, and the next 9 being the state after placing a move.

another question I have in terms of when you teach the neural network, would you feed it the old state and then the state after both you and the opponent have made a move?al networks, so they can play against each other and teach themselves

Second Problem

This next potential problem i have is how I use my threshold and exploration values to choose whether to pick a random action or one the neural network chooses. I increase my threshold linearly from 0 to 1 throughout the iterations. while exploration is a random value between 0 and 1. is this correct? or is there a better way of doing it?

Any feedback would be greatly appreciated, and if anyone has any problems with my question such as it being unclear, not making sense or anything else please let me know so i can fix it

thank you for all who take the time out to try and help.