I'm figuring out how to manipulate convolutional neural networks (CNN) in python and I want to apply this kind of NN to an agent player that plays tic tac toe. I know that's weird and the problem doesn't need some elaborate and complex solutions like CNN, but I'm using this environment just to learn better and compare with the training of a MLP that I implemented.
So, I'm trying to think about how to represent the board correctly as an input to the CNN. Unlike the chess board which we can think the input as 8x8x6 (8x8 as the 2d array representing the board and 6 channels which one representing the different pieces of the game), the tic tac toe is a bit more complicated for me because there are just one kind of piece. Is it possible and correct to represent the X and O as different pieces? Has anyone implemented something like this?