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We agree with Lake and colleagues on their list of key ingredients forbuilding humanlike intelligence, including the idea that model-based reasoningis essential. However, we favor an approach that centers on one additionalingredient: autonomy. In particular, we aim toward agents that can both buildand exploit their own internal models, with minimal human hand-engineering. Webelieve an approach centered on autonomous learning has the greatest chance ofsuccess as we scale toward real-world complexity, tackling domains for whichready-made formal models are not available. Here we survey several importantexamples of the progress that has been made toward building autonomous agentswith humanlike abilities, and highlight some outstanding challenges.

Building Machines that Learn and Think for Themselves: Commentary on Lake et al., Behavioral and Brain Sciences, 2017