title: AI backpropagation for a game
body: <p>This question does not have code examples, I'm looking for an approach on how to do this.</p>
  
  <p>Imagine a neural network trying to learn a game, it has 4 possible outputs (moves it can do).</p>
  
  <p>In case the other player wins or gains an advantage after a (bad) move from the neural network you might want do backpropagation to teach it NOT to make this move. So you'd want to input the data [?, 0, ?, ?] to the cost function. 
  ... but because any other move might be OK or might not be I don't have values to input for the other moves. 
  [1, 0, 1, 1] is not what I want.</p>
  
  <p>How could you do the backpropagation on just 1 output? Does DeepLearning4J cater for this situation?</p>
  
  <p>Thanks for any help!</p>
  
  <p>R.</p>