By adjusting the value of the unobserved state penalty u, we can adjust the extent to which this model follows the supervised policy defined by S data (s, a) or the reinforcement learning policy defined by Q data (s, a).
if u is very low, then maximizing Q hybrid (s, a) is equivalent to maximizing S data (s, a).