Hello!

I've tried recently to solve the ConnectFour game using reinforcement learning (SARSA algorithm). I'm familiar with this method, but I have a big problem with the state space of this game. I identify a table board as a matrix (with 6 rows and 7 columns) and I need a method to classify similar matrix in order to minimize the state space (otherwise the learning algorithm will not learn). I tried with an artificial neural network. In fact, this is a back-propagation network with 126 input nodes (3 for every cell in the matrix -> coresponding to Red,Black or free cell). In the hidden layer I put 84 neurons and the output layer has 42 nodes.

Unfortunately, to work with back-propagation I need to know the classed for the training examples, but I don't and the classification is very poor.

Maybe you can help me with some hints. Also I want to know whether this ANN is good enough and what other methods can I use to classify the states (in order to minimize the state space)?

Thanks a lot,

MrRed