How did we get the artificial neural networks to play noughts and crosses (tic tac toe)?
Just like the evolving Travelling Salesman solutions we experimented with the noughts and crosses neural networks had no understanding of the game they were playing. There was no built in knowledge although we did adapt the neural network structure to allow an opportunity for the networks to evolve a response to the relative positions of the markers in the game as it progressed. For each round the Input neurons were set to +1 for each position that the neural network had a marker and 1 for each position occupied by its opponents marker. Empty cells were set to 0 (zero). Once the values had been propagated through the network then the output states of the Output layer neurons were read. The playing choice of the network was deemed to be the one with the highest value (in the range 0 to 1) associated with an empty playing position. Output values for cells already occupied in previous rounds were ignored. We later changed this process and read a single value from a single output neuron th
