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

The main problem I see here is one of training. You say you want your ANN to take the current board position and evaluate how good it is for a player. (I assume you will take every possible move for a player, apply it to the current board state, evaluate via the ANN and then take the one with the highest output - ie: hill climbing)

Your options as I see them are:

• Develop some heuristic function to evaluate the board state and train the network off that. But that begs the question of why use an ANN at all, when you could just use your heuristic.

• Use some statistical measure such as "How many games were won by white or black from this board configuration?", which would give you a fitness value between white or black. The difficulty with that is the amount of training data required for the size of your problem space.

With the second option you could always feed it board sequences from grandmaster games and hope there is enough coverage for the ANN to develop a solution.

Due to the complexity of the problem I'd want to throw the largest network (ie: lots of internal nodes) at it as I could without slowing down the training too much.