The big pictures in this case is: You use a neuronal network to decide at each step to flap the birds wings or not. That is the only output. The input is only

The big pictures in this case is: You use a neuronal network to decide at each step to flap the birds wings or not. That is the only output. The input is only the birds height (y-position) and the height of the next hole. (https://en.wikipedia.org/wiki/Feedforward_neural_network https://en.wikipedia.org/wiki/Feedforward_neural_network) The question now is how to find the correct weights for the net. That net is not trained in a traditional supervised way like with gradient descent (which would be more complicated). Instead it uses a genetic algorithms to find new weights for neuronal networks of future generations. (https://en.wikipedia.org/wiki/Genetic_algorithm https://en.wikipedia.org/wiki/Genetic_algorithm) And that's basically it in this case.