My high-level takeaway from Matthew Lai's Giraffe Chess Paper is that one would want to use broad, shallow game trees, with some method of evaluating the probability of a favorable outcome for a given board position.  Is this correct?  (Still working my way though the AlphaGo paper, but the method seems to be similar.) 
Giraffe Chess - High Level Assessment
machine learning