How to program a neural network for chess?

Question

I want to program a chess engine which learns to make good moves and win against other players. I\'ve already coded a representation of the chess board and a function which outp

Answer 1

What you need to train a ANN is either something like backpropagation learning or some form of a genetic algorithm. But chess is such an complex game that it is unlikly that a simple ANN will learn to play it - even more if the learning process is unsupervised.

Further, your question does not say anything about the number of layers. You want to use 385 input neurons to encode the current situation. But how do you want to decide what to do? On neuron per field? Highest excitation wins? But there is often more than one possible move.

Further you will need several hidden layers - the functions that can be represented with an input and an output layer without hidden layer are really limited.

So I do not want to prevent you from trying it, but chances for a successful implemenation and training within say one year or so a practically zero.

I tried to build and train an ANN to play Tic-tac-toe when I was 16 years or so ... and I failed. I would suggest to try such an simple game first.