Building Machines that Learn and Think for Themselves: Commentary on
  Lake et al., Behavioral and Brain Sciences, 2017
  We agree with Lake and colleagues on their list of key ingredients for
building humanlike intelligence, including the idea that model-based reasoning
is essential. However, we favor an approach that centers on one additional
ingredient: autonomy. In particular, we aim toward agents that can both build
and exploit their own internal models, with minimal human hand-engineering. We
believe an approach centered on autonomous learning has the greatest chance of
success as we scale toward real-world complexity, tackling domains for which
ready-made formal models are not available. Here we survey several important
examples of the progress that has been made toward building autonomous agents
with humanlike abilities, and highlight some outstanding challenges.
