I'm wondering how to train a neural network for a round based board game like, tic-tac-toe, chess, risk or any other round based game. Getting the next move by inference seems to be pretty straight forward, by feeding the game state as input and using the output as the move for the current player. However training an AI for that purpose doesn't appear to be that straight forward, because:
- There might not be a rating if a single move is good or not, so training of single moves doesn't seem to be the right choice
- Using all game states (inputs) and moves (outputs) of the whole game to train the neural network, doesn't seem to be the right choice as not all moves within a lost game might be bad
So I'm wondering how to train a neural network for a round based board game? I would like to create a neural network for tic-tac-toe using tensorflow.