Learning a hierarchy
It seems to me there's been an interesting turn in AI recently, toward focusing on adaptability as a goal in itself. Deep learning has shown that there is incredible power in stochastic gradient descent over a space of functions, but so far that has mostly been applied to rigid tasks. Now work like this is about turning that power towards adaptability itself as a goal, and it seems to me that this brings us towards "real" intelligence.<p>The logical extreme of this thinking would be agents that actually maximize entropy of future actions as the only objective function, like in [1]<p>[1] <a href="http://paulispace.com/intelligence/2017/07/06/maxent.html" rel="nofollow">http://paulispace.com/intelligence/2017/07/06/maxent.html</a>